autoresearch.jsonl

{"type":"config","name":"Optimize DFlash DDTree TPS on Castle","metricName":"tps","metricUnit":"","bestDirection":"higher"}
{"run":1,"commit":"b63fd0d","metric":0,"metrics":{"tps":0},"status":"crash","description":"baseline harness failed before benchmark during sync/ssh setup","timestamp":1777494462566,"segment":0,"confidence":null,"asi":{"hypothesis":"establish Castle e2e baseline using local-to-remote sync and CUDA harness","rollback_reason":"script exited with ssh/rsync code 255 before producing output","next_action_hint":"debug autoresearch.sh sync command; likely rsync invoking ssh differently than direct ssh"}}
{"run":2,"commit":"b63fd0d","metric":0,"metrics":{"tps":0},"status":"crash","description":"baseline harness failed due shell quoting in remote kill command","timestamp":1777494502610,"segment":0,"confidence":null,"asi":{"hypothesis":"fix pkill self-termination in Castle benchmark harness","rollback_reason":"bash expanded $1 locally under set -u in the awk kill snippet","next_action_hint":"escape awk field as \\$1 or avoid awk entirely with pgrep pattern"}}
{"run":3,"commit":"0374171","metric":0.665751,"metrics":{"tps":0.665751,"spec_sec":24.033,"gen_tokens":16,"steps":9,"committed":0,"step_ms":282.13,"pack_ms":10.25,"draft_ms":203.26,"topk_ms":20.85,"exact_ms":47.73,"exact_decode_ms":0,"acceptance":1.889},"status":"keep","description":"baseline Castle e2e chain-only DDTree benchmark with 1024 target feature window","timestamp":1777494603864,"segment":0,"confidence":null,"asi":{"hypothesis":"establish baseline using current stable chain-only exact validation, full target/draft GPU offload, q4 KV, 64k ctx, real rendered prompt","benchmark":"./autoresearch.sh on Castle; gen=16; prompt=/tmp/real_rendered_prompt.txt; LLAMA_DDTREE_TARGET_FEAT_CTX=1024","note":"committed parser returned 0 likely due regex choosing absent/overwritten field; acceptance parsed from e2e output is the useful commit-rate signal"}}
{"type":"config","name":"Optimize DFlash DDTree decode TPS on Castle","metricName":"tps","metricUnit":"","bestDirection":"higher"}
{"run":4,"commit":"6510b31","metric":6.419361,"metrics":{"tps":6.419361,"e2e_tps":1.197874,"spec_sec":26.714,"gen_tokens":32,"steps":18,"committed":0,"step_ms":276.94,"pack_ms":8.88,"draft_ms":201.75,"topk_ms":20.64,"exact_ms":45.63,"exact_decode_ms":0,"acceptance":1.833},"status":"keep","description":"decode-TPS baseline with gen32 after fixing primary metric to exclude prompt/model overhead","timestamp":1777494737663,"segment":1,"confidence":null,"asi":{"hypothesis":"use decode-only TPS as the primary metric because current optimization target is per-step decode cost, not prompt prefill/model load","benchmark":"Castle e2e gen=32, real_rendered_prompt, 64k ctx, q4 KV, target_feat_ctx=1024","note":"committed parser still reports 0 due escaped whitespace regex; output shows committed=33, fix parser next"}}
{"run":5,"commit":"6510b31","metric":6.32999,"metrics":{"tps":6.32999,"e2e_tps":1.207183,"spec_sec":26.508,"gen_tokens":32,"steps":18,"committed":33,"step_ms":280.85,"pack_ms":8.91,"draft_ms":204.58,"topk_ms":21.5,"exact_ms":45.83,"exact_decode_ms":0,"acceptance":1.833},"status":"discard","description":"fix committed metric parser; benchmark noise slightly lower than baseline","timestamp":1777494820583,"segment":1,"confidence":null,"asi":{"hypothesis":"correct benchmark committed-token parsing without changing runtime code","rollback_reason":"primary decode TPS was slightly worse than baseline, likely noise; no runtime optimization tested","next_action_hint":"parser fix is in autoresearch.sh and should be preserved as an autoresearch file; proceed to source-level optimization"}}
{"run":6,"commit":"73f2fb0","metric":7.73072,"metrics":{"tps":7.73072,"e2e_tps":1.251564,"spec_sec":25.568,"gen_tokens":32,"steps":17,"committed":33,"step_ms":243.49,"pack_ms":4.49,"draft_ms":171.03,"topk_ms":19.51,"exact_ms":48.43,"exact_decode_ms":0,"acceptance":1.941},"status":"keep","description":"benchmark target feature window 512 for lower draft/pack cost","timestamp":1777494901661,"segment":1,"confidence":14.673204954627211,"asi":{"hypothesis":"smaller DFlash target feature context may reduce pack/upload and draft compute enough to improve decode TPS on the real rendered prompt","result":"LLAMA_DDTREE_TARGET_FEAT_CTX=512 improved decode TPS from 6.42 to 7.73; pack 8.88->4.49 ms, draft 201.75->171.03 ms, acceptance 1.83->1.94","next_action_hint":"confirm 512 on repeated run and test 256/768; if stable, consider default/window recommendation for server workload"}}
{"run":7,"commit":"2a8eba2","metric":8.388756,"metrics":{"tps":8.388756,"e2e_tps":1.262128,"spec_sec":25.354,"gen_tokens":32,"steps":17,"committed":33,"step_ms":224.39,"pack_ms":2.24,"draft_ms":154.39,"topk_ms":19.77,"exact_ms":47.96,"exact_decode_ms":0,"acceptance":1.941},"status":"keep","description":"benchmark target feature window 256 for further draft/pack reduction","timestamp":1777494974670,"segment":1,"confidence":2.8119551947912877,"asi":{"hypothesis":"target feature context can be reduced below 512 on this prompt without hurting proposal quality, further lowering draft compute and pack cost","result":"256 improved decode TPS to 8.39; draft dropped to 154 ms and pack to 2.24 ms with same acceptance as 512","next_action_hint":"test 128 and 384; watch acceptance/regressions because too short a feature window may harm draft quality on broader prompts"}}
{"run":8,"commit":"3f125a4","metric":8.751467,"metrics":{"tps":8.751467,"e2e_tps":1.277649,"spec_sec":25.046,"gen_tokens":32,"steps":17,"committed":33,"step_ms":215.09,"pack_ms":1.09,"draft_ms":144.76,"topk_ms":20.79,"exact_ms":48.41,"exact_decode_ms":0,"acceptance":1.941},"status":"keep","description":"benchmark target feature window 128","timestamp":1777495047214,"segment":1,"confidence":2.2847052207843856,"asi":{"hypothesis":"a 128-token target feature window may retain enough recent signal while reducing draft attention and upload cost","result":"128 improved decode TPS to 8.75; draft 144.76 ms, pack 1.09 ms, acceptance unchanged vs 256/512","next_action_hint":"test 64 and longer generation/prompt coverage before changing default; risk is hidden acceptance drop on other prompts"}}
{"run":9,"commit":"3f125a4","metric":8.481742,"metrics":{"tps":8.481742,"e2e_tps":1.274139,"spec_sec":25.115,"gen_tokens":32,"steps":17,"committed":33,"step_ms":221.93,"pack_ms":0.47,"draft_ms":153.01,"topk_ms":20.45,"exact_ms":47.96,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark target feature window 64; pack lower but draft slower than 128","timestamp":1777495120133,"segment":1,"confidence":4.187908592095226,"asi":{"hypothesis":"shrinking target feature window below 128 may further reduce pack and draft context work","rollback_reason":"64 lowered pack to 0.47 ms but draft compute rose to 153 ms and decode TPS fell below the 128-window best","next_action_hint":"treat 128 as the current sweet spot on this prompt; test 96/160 only if tuning window further matters"}}
{"run":10,"commit":"3f125a4","metric":7.958279,"metrics":{"tps":7.958279,"e2e_tps":1.256676,"spec_sec":25.464,"gen_tokens":32,"steps":19,"committed":33,"step_ms":211.63,"pack_ms":0.79,"draft_ms":147.96,"topk_ms":19.88,"exact_ms":42.96,"exact_decode_ms":0,"acceptance":1.737},"status":"discard","description":"benchmark target feature window 96; lower per-step cost lost acceptance","timestamp":1777495203736,"segment":1,"confidence":4.455149647635071,"asi":{"hypothesis":"96-token target feature context might sit between 64 and 128 with lower draft cost but enough proposal quality","rollback_reason":"acceptance dropped from 1.94 to 1.74 and required 19 steps; decode TPS below 128-window best","next_action_hint":"128 remains better than smaller windows for this prompt; test 160/192 or move to non-window optimizations"}}
{"run":11,"commit":"3f125a4","metric":8.742524,"metrics":{"tps":8.742524,"e2e_tps":1.276935,"spec_sec":25.06,"gen_tokens":32,"steps":17,"committed":33,"step_ms":215.31,"pack_ms":1.34,"draft_ms":147.17,"topk_ms":18.84,"exact_ms":47.92,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark target feature window 160; tied 128 within noise but no improvement","timestamp":1777495276127,"segment":1,"confidence":4.609797945056553,"asi":{"hypothesis":"160-token window may reduce noise versus 128 while keeping acceptance and similar draft cost","rollback_reason":"decode TPS was effectively tied but below the 128-window best; no primary improvement","next_action_hint":"128/160 are close; choose 128 for lower memory/pack unless longer prompt validation favors 160"}}
{"run":12,"commit":"3f125a4","metric":8.341175,"metrics":{"tps":8.341175,"e2e_tps":1.263873,"spec_sec":25.319,"gen_tokens":32,"steps":17,"committed":33,"step_ms":225.67,"pack_ms":1.61,"draft_ms":155.69,"topk_ms":20.27,"exact_ms":48.07,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark target feature window 192; slower draft than 128/160","timestamp":1777495349316,"segment":1,"confidence":5.810668520414904,"asi":{"hypothesis":"192-token window may retain proposal quality while staying much cheaper than 256/512","rollback_reason":"acceptance matched 128 but draft/step time regressed, so primary TPS fell","next_action_hint":"do not tune larger windows for this prompt unless broader validation shows 128 harms acceptance"}}
{"run":13,"commit":"3f125a4","metric":8.477158,"metrics":{"tps":8.477158,"e2e_tps":1.282257,"spec_sec":24.956,"gen_tokens":32,"steps":17,"committed":33,"step_ms":222.05,"pack_ms":1.08,"draft_ms":153.39,"topk_ms":19.58,"exact_ms":47.97,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"default target feature window 128 plus smaller draft context","timestamp":1777495532959,"segment":1,"confidence":6.104510117006526,"asi":{"hypothesis":"make 128 the code default and size draft n_ctx to target feature window + block so server avoids oversized draft context","rollback_reason":"primary decode TPS was below the prior 128-window env best despite lower set_inputs; draft compute/noise dominated and source change did not improve best","next_action_hint":"revisit draft n_ctx sizing separately with repeated runs; the log showed draft n_ctx=256 and set_inputs ~0.7 ms vs ~4 ms, but step time was not better"}}
{"run":14,"commit":"3f125a4","metric":8.572515,"metrics":{"tps":8.572515,"e2e_tps":1.275053,"spec_sec":25.097,"gen_tokens":32,"steps":17,"committed":33,"step_ms":219.58,"pack_ms":1.08,"draft_ms":149.11,"topk_ms":20.98,"exact_ms":48.38,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"replace small-K heap top-k with fixed array scan","timestamp":1777495681069,"segment":1,"confidence":6.592190362045204,"asi":{"hypothesis":"avoid per-row heap allocation/maintenance in extract_top_k_logprobs for K=8 using fixed stack arrays","rollback_reason":"topk time increased to 20.98 ms and primary TPS remained below the 128-window best; std heap path is not the bottleneck or is better optimized","next_action_hint":"future top-k gains likely need GPU-side logits processing or avoiding logsumexp/scanning, not a small CPU data structure tweak"}}
{"run":15,"commit":"3f125a4","metric":8.708952,"metrics":{"tps":8.708952,"e2e_tps":1.275764,"spec_sec":25.083,"gen_tokens":32,"steps":17,"committed":33,"step_ms":216.14,"pack_ms":1.09,"draft_ms":151.15,"topk_ms":16.14,"exact_ms":47.73,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark budget 14 with 128-window; lower top-k cost but no TPS win","timestamp":1777495763704,"segment":1,"confidence":7.965359774029058,"asi":{"hypothesis":"budget 14 triggers cheaper K=1/argmax proposal extraction while preserving the same accepted chain on this prompt","rollback_reason":"topk dropped 20.8->16.1 ms but total step time did not beat the 128-window budget-22 best; likely draft/noise dominates","next_action_hint":"test budget 8/1 only if looking for lower overhead mode; budget 14 is close but not a primary improvement"}}
{"run":16,"commit":"3f125a4","metric":8.433481,"metrics":{"tps":8.433481,"e2e_tps":1.267578,"spec_sec":25.245,"gen_tokens":32,"steps":17,"committed":33,"step_ms":223.2,"pack_ms":1.08,"draft_ms":156.77,"topk_ms":17.67,"exact_ms":47.64,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark budget 8 with 128-window; slower than budget 14/22","timestamp":1777495844676,"segment":1,"confidence":8.4658857012172,"asi":{"hypothesis":"smaller budget may reduce proposal overhead without reducing accepted chain length in exact-validation mode","rollback_reason":"budget 8 had same step count but slower draft/topk aggregate than budget 14 and below best TPS","next_action_hint":"budget tuning is not the next major path; keep budget 22 or 14 and focus draft/exact decode"}}
{"run":17,"commit":"3f125a4","metric":8.123665,"metrics":{"tps":8.123665,"e2e_tps":1.582756,"spec_sec":26.536,"gen_tokens":42,"steps":24,"committed":42,"step_ms":215.42,"pack_ms":1.02,"draft_ms":150.09,"topk_ms":20.84,"exact_ms":43.43,"exact_decode_ms":0,"acceptance":1.75},"status":"discard","description":"confirm 128-window on longer gen request; generation ended at 42 tokens and TPS lower","timestamp":1777495921126,"segment":1,"confidence":7.969102337827434,"asi":{"hypothesis":"longer generation should reduce noise and confirm whether 128-window remains best beyond a 32-token sample","rollback_reason":"request stopped after 42 generated tokens and acceptance fell to 1.75; decode TPS below current best","next_action_hint":"use a non-EOS prompt or different fixture for long-generation confirmation; current rendered prompt is not ideal for 64-token stability"}}
{"run":18,"commit":"c2c95e3","metric":9.112863,"metrics":{"tps":9.112863,"e2e_tps":1.2838,"spec_sec":24.926,"gen_tokens":32,"steps":17,"committed":33,"step_ms":206.56,"pack_ms":1.06,"draft_ms":137.65,"topk_ms":19.8,"exact_ms":48.01,"exact_decode_ms":0,"acceptance":1.941},"status":"keep","description":"change DDTree default target feature window to 128","timestamp":1777496003711,"segment":1,"confidence":8.71562209789579,"asi":{"hypothesis":"make the observed 128-token target feature window the default so server/e2e use the faster draft context without requiring an env override","result":"default 128 produced the best run so far: 9.11 decode TPS, draft 137.65 ms, pack 1.06 ms, acceptance unchanged at 1.94","next_action_hint":"validate on additional prompts before treating 128 as globally safe; env knob still allows raising to 512/1024 if acceptance drops"}}
{"run":19,"commit":"c2c95e3","metric":8.611341,"metrics":{"tps":8.611341,"e2e_tps":1.273784,"spec_sec":25.122,"gen_tokens":32,"steps":17,"committed":33,"step_ms":218.59,"pack_ms":1.07,"draft_ms":149.86,"topk_ms":19.62,"exact_ms":48.01,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"repeat default 128-window run for noise check","timestamp":1777496086262,"segment":1,"confidence":9.96049456675487,"asi":{"hypothesis":"re-run the kept 128 default to estimate noise and verify improvement is not a one-off","rollback_reason":"repeat was below the 9.11 best but still far above the original 1024-window baseline; no new code changes to keep","next_action_hint":"treat 128 default as real but noisy; future comparisons should beat about 8.6-9.1 decode TPS"}}
{"run":20,"commit":"c2c95e3","metric":8.819946,"metrics":{"tps":8.819946,"e2e_tps":1.273885,"spec_sec":25.12,"gen_tokens":32,"steps":17,"committed":33,"step_ms":213.42,"pack_ms":1.09,"draft_ms":144.99,"topk_ms":19.36,"exact_ms":47.94,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"disable DDTree micro-profile logging during benchmark","timestamp":1777496178429,"segment":1,"confidence":10.150139806908188,"asi":{"hypothesis":"LLAMA_DDTREE_PROFILE logging may add per-step overhead, so production benchmarking should disable it","rollback_reason":"no-profile run did not beat the kept 9.11 TPS best, though it remained above baseline","next_action_hint":"keep profiling disabled for user-facing server unless collecting diagnostics; script knob is preserved in autoresearch.sh"}}
{"run":21,"commit":"c2c95e3","metric":8.471256,"metrics":{"tps":8.471256,"e2e_tps":1.271052,"spec_sec":25.176,"gen_tokens":32,"steps":18,"committed":33,"step_ms":209.86,"pack_ms":1.08,"draft_ms":151.2,"topk_ms":12.38,"exact_ms":45.18,"exact_decode_ms":0,"acceptance":1.833},"status":"discard","description":"diagnostic dynamic DDTree block size 8","timestamp":1777496331268,"segment":1,"confidence":10.70842957726881,"asi":{"hypothesis":"smaller draft block size may reduce draft/top-k compute enough to offset lower speculative horizon","rollback_reason":"block size 8 reduced topk but acceptance dropped and an extra step was needed; primary TPS below current 128-window default","next_action_hint":"keep block size 16; reducing block size does not help this prompt"}}
{"run":22,"commit":"c2c95e3","metric":8.249464,"metrics":{"tps":8.249464,"e2e_tps":1.263823,"spec_sec":25.32,"gen_tokens":32,"steps":19,"committed":33,"step_ms":204.16,"pack_ms":0.23,"draft_ms":141.61,"topk_ms":19.45,"exact_ms":42.84,"exact_decode_ms":0,"acceptance":1.737},"status":"discard","description":"benchmark target feature window 32; too little context hurts acceptance","timestamp":1777496404861,"segment":1,"confidence":11.331709410339274,"asi":{"hypothesis":"very small target feature window may lower draft compute enough to compensate for weaker proposals","rollback_reason":"acceptance dropped to 1.74 and 19 steps were needed, so TPS stayed below the 128 default","next_action_hint":"do not go below 128 for this workload unless a broader prompt shows different behavior"}}
{"run":23,"commit":"c2c95e3","metric":8.67164,"metrics":{"tps":8.67164,"e2e_tps":1.279284,"spec_sec":25.014,"gen_tokens":32,"steps":17,"committed":33,"step_ms":217.07,"pack_ms":1.07,"draft_ms":151.99,"topk_ms":16.08,"exact_ms":47.9,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"use K=1 proposal extraction for default exact-validation path","timestamp":1777496508196,"segment":1,"confidence":11.723927501915169,"asi":{"hypothesis":"when batched tree verify is disabled, default exact validation can use a top-1 draft chain instead of K=8 tree proposals to reduce top-k overhead while remaining correct","rollback_reason":"topk improved by ~3.7 ms but total step time stayed below the 128-window best because draft compute/noise dominated","next_action_hint":"K=1 is a possible conservative mode but not a net win in this benchmark; do not keep as default"}}
{"run":24,"commit":"c2c95e3","metric":8.675637,"metrics":{"tps":8.675637,"e2e_tps":1.271102,"spec_sec":25.175,"gen_tokens":32,"steps":17,"committed":33,"step_ms":216.97,"pack_ms":1.06,"draft_ms":148.41,"topk_ms":19.69,"exact_ms":47.77,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"cache DFlash mask token embedding in DDTree driver","timestamp":1777496601681,"segment":1,"confidence":11.829481672771372,"asi":{"hypothesis":"avoid per-step mask embedding lookup/allocation when building draft noise embeddings","rollback_reason":"change was correct but primary TPS did not beat the 128-window best; mask embedding work is not a measurable bottleneck","next_action_hint":"focus on draft graph compute or exact target decode rather than small CPU setup around noise embeddings"}}
{"run":25,"commit":"c2c95e3","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.707,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.58,"draft_ms":152.52,"topk_ms":18.22,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"fast-batched fast-rollback at 128-window still OOMs persist on 64k full-draft","timestamp":1777496697475,"segment":1,"confidence":11.829481672771372,"asi":{"hypothesis":"smaller target feature window might free enough memory for fast rollback persist with -ngl65 -ngld6 -c65536","rollback_reason":"persist allocation still failed needing 1707.75 MiB; with SNAPSHOT_FALLBACK=0 driver returned empty output","next_action_hint":"fast rollback remains nonviable for full-draft 64k on this 24GB GPU unless memory is freed elsewhere; test q4/tq3 or reduced draft offload only if willing to trade draft speed"}}
{"run":26,"commit":"c2c95e3","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":0,"gen_tokens":0,"steps":0,"committed":0,"step_ms":0,"pack_ms":0,"draft_ms":0,"topk_ms":0,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"try tq3 KV to fit fast rollback persist; e2e harness does not accept tq3_0","timestamp":1777496743075,"segment":1,"confidence":11.829481672771372,"asi":{"hypothesis":"TQ3 KV might free enough VRAM for fast rollback persist with full target/draft offload","rollback_reason":"test-speculative-tree-e2e only accepts its hardcoded KV type set and rejected --kv-type tq3_0","next_action_hint":"add tq3_0 support to e2e parser before testing this; do not infer runtime viability from this crash"}}
{"run":27,"commit":"c2c95e3","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":26.717,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.47,"draft_ms":153,"topk_ms":22.52,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"add tq3_0 e2e parser support and retry fast rollback; persist still OOMs","timestamp":1777496853671,"segment":1,"confidence":11.829481672771372,"asi":{"hypothesis":"with e2e tq3_0 support, smaller KV cache may fit the 1.7 GiB fast rollback persist buffer","rollback_reason":"tq3_0 run still failed CUDA persist allocation for 1707.75 MiB and returned empty output with snapshot fallback disabled","next_action_hint":"fast rollback requires a larger memory reduction than q4->tq3 KV provides in this harness; avoid more persist-fit tests unless freeing draft layers or compressing persist"}}
{"run":28,"commit":"c2c95e3","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.704,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.52,"draft_ms":279.6,"topk_ms":16.26,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"fast rollback with draft GPU layers 4 still OOMs persist","timestamp":1777496939181,"segment":1,"confidence":11.829481672771372,"asi":{"hypothesis":"offloading fewer draft layers may free VRAM for fast rollback persist while retaining enough draft speed","rollback_reason":"ngld4 still failed 1707.75 MiB persist allocation and draft time already rose to 280 ms","next_action_hint":"if testing persist-fit, drop to ngld3 or lower, but expected draft slowdown likely outweighs rollback savings"}}
{"run":29,"commit":"c2c95e3","metric":4.278956,"metrics":{"tps":4.278956,"e2e_tps":1.114323,"spec_sec":28.717,"gen_tokens":32,"steps":18,"committed":33,"step_ms":415.47,"pack_ms":1.09,"draft_ms":294.24,"topk_ms":17.17,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.833},"status":"discard","description":"fast rollback with draft GPU layers 3 fits but is slower than exact path","timestamp":1777497015792,"segment":1,"confidence":11.723927501915169,"asi":{"hypothesis":"ngld3 may free enough VRAM for fast rollback and remove exact decode cost","rollback_reason":"persist fit and exact cost dropped to zero, but draft slowed to 294 ms and target_tree/rollback path made step 415 ms; TPS far below exact default","next_action_hint":"do not trade draft GPU layers for fast rollback on 64k; full draft GPU exact path is better"}}
{"run":30,"commit":"c2c95e3","metric":8.740901,"metrics":{"tps":8.740901,"e2e_tps":1.289127,"spec_sec":24.823,"gen_tokens":32,"steps":17,"committed":33,"step_ms":215.35,"pack_ms":1.07,"draft_ms":147.03,"topk_ms":19.45,"exact_ms":47.77,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark 32k context for 20k prompt with 128 default","timestamp":1777497087757,"segment":1,"confidence":11.620240385859825,"asi":{"hypothesis":"if the prompt fits under 32k, lower target context may reduce memory/compute overhead versus 64k","rollback_reason":"32k context was above baseline but below the 64k 128-window best; no primary improvement in this e2e workload","next_action_hint":"context reduction may still help server prefill/memory, but decode step optimization should focus elsewhere"}}
{"run":31,"commit":"c2c95e3","metric":8.538297,"metrics":{"tps":8.538297,"e2e_tps":1.284779,"spec_sec":24.907,"gen_tokens":32,"steps":17,"committed":33,"step_ms":220.46,"pack_ms":1.09,"draft_ms":151.06,"topk_ms":20.14,"exact_ms":48.13,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"benchmark 24k context for 20k prompt","timestamp":1777497161415,"segment":1,"confidence":11.723927501915169,"asi":{"hypothesis":"context just above prompt length may reduce decode overhead further than 32k/64k","rollback_reason":"decode TPS below current best; smaller n_ctx did not improve step time on this harness","next_action_hint":"do not spend more iterations on n_ctx for decode TPS; use n_ctx tuning only for memory/server fit"}}
{"run":32,"commit":"c2c95e3","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.44,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.54,"draft_ms":146.12,"topk_ms":20.51,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"smaller draft context plus full-draft fast rollback still OOMs persist","timestamp":1777497248234,"segment":1,"confidence":11.723927501915169,"asi":{"hypothesis":"sizing draft n_ctx to the 128 target-feature window may free enough compute-buffer VRAM for full-draft fast rollback","rollback_reason":"fast rollback still failed persist allocation and returned empty output with snapshot fallback disabled","next_action_hint":"draft context sizing alone does not free the required 1.7 GiB; persist compression is needed for this route"}}
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{"run":57,"commit":"abe969d","metric":8.99928,"metrics":{"tps":8.99928,"e2e_tps":1.257022,"spec_sec":25.457,"gen_tokens":32,"steps":16,"committed":33,"step_ms":222.24,"pack_ms":1.08,"draft_ms":149.56,"topk_ms":20.23,"exact_ms":51.33,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"repeat DDTree budget 32 to confirm previous best against noise","timestamp":1777500057910,"segment":1,"confidence":19.196128504310348,"asi":{"hypothesis":"repeat budget 32 because the previous 9.82 TPS improvement may include noise; confirm whether the step-count/acceptance gain is stable","rollback_reason":"repeat preserved the 16-step and 2.06 acceptance behavior but step time regressed to 222 ms, so primary TPS was below the kept best","next_action_hint":"budget 32 still looks structurally useful via fewer steps, but compare future ideas against a noisy 9.0-9.8 TPS range rather than a single best run"}}
{"run":58,"commit":"abe969d","metric":9.0151,"metrics":{"tps":9.0151,"e2e_tps":1.280307,"spec_sec":24.994,"gen_tokens":32,"steps":16,"committed":33,"step_ms":221.85,"pack_ms":1.07,"draft_ms":148.88,"topk_ms":20.24,"exact_ms":51.62,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test DDTree budget 30 between budget 28 and 32","timestamp":1777500149659,"segment":1,"confidence":19.077213862263655,"asi":{"hypothesis":"budget 30 may keep the 16-step acceptance gain from budget 32 while trimming proposal overhead versus larger budgets","rollback_reason":"budget 30 matched the 16-step/2.06 acceptance pattern but step time stayed around 222 ms and primary TPS remained below the kept budget-32 best","next_action_hint":"budget 30/28/40 do not beat budget 32; try budget 34/36 or switch away from budget tuning if repeats remain noisy"}}
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{"run":61,"commit":"abe969d","metric":8.570174,"metrics":{"tps":8.570174,"e2e_tps":1.266524,"spec_sec":25.266,"gen_tokens":32,"steps":17,"committed":33,"step_ms":219.64,"pack_ms":1.35,"draft_ms":150.5,"topk_ms":19.51,"exact_ms":48.24,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"test budget 32 with target feature window 160","timestamp":1777500462376,"segment":1,"confidence":18.755483015403495,"asi":{"hypothesis":"with the larger budget-32 proposal tree, a slightly longer target-feature window may improve draft proposal quality enough to offset extra pack/draft cost","rollback_reason":"target_feat_ctx=160 lost the budget-32 structural gain: steps rose from 16 to 17 and acceptance fell to 1.94, so TPS dropped","next_action_hint":"keep target feature window at 128 for budget-32; do not combine larger windows with larger budget on this workload"}}
{"run":62,"commit":"abe969d","metric":9.649133,"metrics":{"tps":9.649133,"e2e_tps":1.291572,"spec_sec":24.776,"gen_tokens":32,"steps":17,"committed":33,"step_ms":195.08,"pack_ms":0.95,"draft_ms":128.19,"topk_ms":18.6,"exact_ms":47.32,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"test budget 32 with smaller target feature window 112","timestamp":1777500568011,"segment":1,"confidence":18.510168209448402,"asi":{"hypothesis":"with budget 32, a smaller 112-token target-feature window may reduce draft compute enough to offset losing some proposal quality","rollback_reason":"draft/step time improved significantly, but steps rose to 17 and acceptance fell to 1.94; primary TPS stayed below the kept budget-32 best of 9.82","next_action_hint":"try an intermediate window such as 120 with budget 32, or repeat 112 if prioritizing lower draft latency over best TPS"}}
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{"run":66,"commit":"abe969d","metric":8.867312,"metrics":{"tps":8.867312,"e2e_tps":1.283903,"spec_sec":24.924,"gen_tokens":32,"steps":17,"committed":33,"step_ms":212.28,"pack_ms":0.96,"draft_ms":143.28,"topk_ms":20.12,"exact_ms":47.89,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"test budget 32 with target feature window 116","timestamp":1777500957905,"segment":1,"confidence":18.510168209448402,"asi":{"hypothesis":"target_feat_ctx=116 may keep most of the draft-cost reduction seen at 112 while recovering some proposal quality toward the 128-window budget-32 path","rollback_reason":"116 kept lower draft cost but still lost the budget-32 structural win: steps stayed 17 and acceptance stayed 1.94, so primary TPS remained below best","next_action_hint":"stop testing sub-128 windows with budget 32; they lower per-step cost but consistently lose the 16-step acceptance behavior"}}
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{"run":69,"commit":"abe969d","metric":9.219989,"metrics":{"tps":9.219989,"e2e_tps":1.28236,"spec_sec":24.954,"gen_tokens":32,"steps":16,"committed":33,"step_ms":216.92,"pack_ms":1.09,"draft_ms":144.92,"topk_ms":19.97,"exact_ms":50.9,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test budget 32 with draft top-k capped at 4","timestamp":1777502096247,"segment":1,"confidence":15.883380263274644,"asi":{"hypothesis":"budget 32 may not need K=8 alternatives per row; capping draft top-k to 4 could preserve the 16-step acceptance behavior while reducing top-k/tree overhead","rollback_reason":"K=4 preserved 16 steps and 2.06 acceptance but primary TPS stayed below the kept budget-32 best; topk did not materially improve","next_action_hint":"top-k cardinality is not the main cost; do not add a TOP_K knob unless needed for diagnostics"}}
{"run":70,"commit":"abe969d","metric":9.147875,"metrics":{"tps":9.147875,"e2e_tps":1.279335,"spec_sec":25.013,"gen_tokens":32,"steps":16,"committed":34,"step_ms":218.63,"pack_ms":1.08,"draft_ms":147.84,"topk_ms":17.36,"exact_ms":52.32,"exact_decode_ms":0,"acceptance":2.125},"status":"discard","description":"cap DDTree proposal rows to 8 for budget 32","timestamp":1777502354709,"segment":1,"confidence":15.856576119639561,"asi":{"hypothesis":"exact-validation path rarely needs all 15 draft rows; capping DDTree proposal rows to 8 may preserve acceptance while reducing CPU top-k scan cost","rollback_reason":"topk improved to 17.36 ms and acceptance stayed strong, but exact cost rose and total step time remained below the kept best; also broad prompts could need deeper rows","next_action_hint":"tree-row capping can reduce topk but is not enough alone; avoid keeping because it risks hurting prompts with long accepted runs"}}
{"run":71,"commit":"abe969d","metric":8.451759,"metrics":{"tps":8.451759,"e2e_tps":1.584547,"spec_sec":26.506,"gen_tokens":42,"steps":23,"committed":42,"step_ms":216.06,"pack_ms":1.03,"draft_ms":149.5,"topk_ms":20.1,"exact_ms":45.4,"exact_decode_ms":0,"acceptance":1.826},"status":"discard","description":"validate budget 32 on longer generation request","timestamp":1777502458355,"segment":1,"confidence":15.883380263274644,"asi":{"hypothesis":"longer generation should check whether the budget-32 16-step gain generalizes beyond the short 32-token sample and reduce overfitting risk","rollback_reason":"the prompt ended at 42 generated tokens and acceptance fell to 1.83; decode TPS below budget-32 short-run best","next_action_hint":"use an additional non-EOS prompt fixture for robust validation; this prompt is useful but not sufficient for long-run budget tuning"}}
{"run":72,"commit":"abe969d","metric":9.227646,"metrics":{"tps":9.227646,"e2e_tps":1.283852,"spec_sec":24.925,"gen_tokens":32,"steps":16,"committed":33,"step_ms":216.74,"pack_ms":1.08,"draft_ms":144.28,"topk_ms":20.3,"exact_ms":51.03,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test pure best-first DDTree without greedy chain seed at budget 32","timestamp":1777502608147,"segment":1,"confidence":15.856576119639561,"asi":{"hypothesis":"chain_seed spends many budget-32 nodes on a deep greedy spine even though exact acceptance averages only about 2 tokens; pure best-first may allocate more shallow alternatives and improve proposal coverage","rollback_reason":"chain_seed=0 preserved the 16-step/2.06 acceptance behavior but did not beat the kept budget-32 best; no primary improvement and it may be less robust on prompts with long greedy runs","next_action_hint":"keep chain_seed enabled; if revisiting tree construction, use a hybrid depth cap rather than disabling the greedy spine entirely"}}
{"run":73,"commit":"abe969d","metric":9.040774,"metrics":{"tps":9.040774,"e2e_tps":1.281897,"spec_sec":24.963,"gen_tokens":32,"steps":16,"committed":33,"step_ms":221.22,"pack_ms":1.09,"draft_ms":148.96,"topk_ms":20.16,"exact_ms":50.98,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"hybrid DDTree chain seed capped to depth 4 at budget 32","timestamp":1777502734449,"segment":1,"confidence":15.776850112479453,"asi":{"hypothesis":"cap the pre-inserted greedy spine to depth 4 so budget-32 keeps robust shallow branch coverage while still preserving enough greedy-chain depth","rollback_reason":"chain-depth cap preserved the 16-step/2.06 acceptance pattern but step time stayed around 221 ms and did not beat the kept budget-32 best","next_action_hint":"hybrid chain-depth capping does not improve this workload; avoid further tree construction tweaks unless using a broader prompt corpus"}}
{"run":74,"commit":"abe969d","metric":9.173891,"metrics":{"tps":9.173891,"e2e_tps":1.284058,"spec_sec":24.921,"gen_tokens":32,"steps":16,"committed":33,"step_ms":218.01,"pack_ms":1.07,"draft_ms":146.71,"topk_ms":19.2,"exact_ms":51,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test budget 32 with target feature window 124","timestamp":1777502840662,"segment":1,"confidence":15.556627806464379,"asi":{"hypothesis":"target_feat_ctx=124 may be the smallest window that preserves the budget-32 16-step acceptance behavior while slightly reducing draft compute versus 128","rollback_reason":"124 preserved 16 steps and 2.06 acceptance, but primary TPS stayed below the kept budget-32 best and within the noisy 9.0-9.2 band","next_action_hint":"128 remains the best kept setting; 124 is viable but not a primary improvement, so move away from window tuning"}}
{"run":75,"commit":"abe969d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.522,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.54,"draft_ms":201.54,"topk_ms":15.37,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"fast rollback budget 14 with draft GPU layers 5","timestamp":1777502969042,"segment":1,"confidence":15.556627806464379,"asi":{"hypothesis":"budget 14 reduces persist to about 1.09 GiB; moving one draft layer off GPU may free enough VRAM for fast rollback while keeping draft faster than the known ngld3 path","rollback_reason":"persist allocation still OOMed at 1086.75 MiB, and draft time already rose to 201 ms with ngld5; no tokens generated","next_action_hint":"do not pursue small draft-offload reductions for persist fit; memory fragmentation or compute buffers still prevent budget14 persist allocation, and draft slowdown erodes expected gains"}}
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{"run":77,"commit":"abe969d","metric":8.99847,"metrics":{"tps":8.99847,"e2e_tps":1.275307,"spec_sec":25.092,"gen_tokens":32,"steps":16,"committed":34,"step_ms":222.26,"pack_ms":1.08,"draft_ms":150.91,"topk_ms":17.85,"exact_ms":52.38,"exact_decode_ms":0,"acceptance":2.125},"status":"discard","description":"cap draft logits outputs to tree rows for budget 32 row-8 proposal","timestamp":1777503251223,"segment":1,"confidence":13.227183816638313,"asi":{"hypothesis":"when capping proposal rows to 8, also avoid requesting draft logits for rows beyond that cap to reduce lm_head/logits work while keeping exact validation authoritative","rollback_reason":"correctness passed and topk remained lower, but draft time increased to 150.91 ms and total TPS fell below the budget-32 best; sparse logits flags do not reduce the dominant draft compute here","next_action_hint":"do not pursue output-row pruning in the draft path; focus on draft internal compute or exact target decode instead"}}
{"run":78,"commit":"abe969d","metric":9.495774,"metrics":{"tps":9.495774,"e2e_tps":1.288245,"spec_sec":24.84,"gen_tokens":32,"steps":16,"committed":33,"step_ms":210.62,"pack_ms":1.09,"draft_ms":138.52,"topk_ms":19.88,"exact_ms":51.09,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test DDTree budget 26 below 28/32 threshold","timestamp":1777503357658,"segment":1,"confidence":12.929750236155215,"asi":{"hypothesis":"budget 26 may be the smallest budget that preserves the 16-step acceptance gain while reducing tree/proposal overhead versus budget 28/32","rollback_reason":"budget 26 preserved 16 steps and improved step time to 210.62 ms, but primary TPS remained below the kept budget-32 best of 9.82","next_action_hint":"budget 26 is promising and less noisy than nearby budgets; test budget 24 or repeat 26 before considering changing the configured default"}}
{"run":79,"commit":"abe969d","metric":9.011039,"metrics":{"tps":9.011039,"e2e_tps":1.284883,"spec_sec":24.905,"gen_tokens":32,"steps":16,"committed":33,"step_ms":221.95,"pack_ms":1.08,"draft_ms":149.2,"topk_ms":19.99,"exact_ms":51.65,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test DDTree budget 24 after promising budget 26","timestamp":1777503455626,"segment":1,"confidence":12.590074250645914,"asi":{"hypothesis":"budget 24 may be the smallest budget that retains the 16-step acceptance gain while lowering overhead more than budget 26","rollback_reason":"budget 24 preserved 16 steps but step time regressed to 221.95 ms and TPS fell well below budget 26 and the kept best","next_action_hint":"budget 26 looks more promising than 24; repeat 26 or test 25/27 if continuing budget tuning"}}
{"run":80,"commit":"abe969d","metric":8.965795,"metrics":{"tps":8.965795,"e2e_tps":1.280974,"spec_sec":24.981,"gen_tokens":32,"steps":16,"committed":33,"step_ms":223.07,"pack_ms":1.07,"draft_ms":149.46,"topk_ms":20.71,"exact_ms":51.79,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"repeat DDTree budget 26 to check noise","timestamp":1777503555898,"segment":1,"confidence":10.891133809356086,"asi":{"hypothesis":"repeat budget 26 because the previous 9.50 TPS result may indicate a smaller-budget sweet spot or may be noise","rollback_reason":"repeat preserved 16-step acceptance but regressed to 8.97 TPS, confirming the earlier 9.50 budget-26 run was mostly noise","next_action_hint":"do not keep budget 26; budget 32 remains the configured best despite noisy single-run highs"}}
{"run":81,"commit":"a4884f4","metric":10.147906,"metrics":{"tps":10.147906,"e2e_tps":1.29749,"spec_sec":24.663,"gen_tokens":32,"steps":14,"committed":33,"step_ms":225.24,"pack_ms":1.12,"draft_ms":145.35,"topk_ms":20.04,"exact_ms":58.69,"exact_decode_ms":0,"acceptance":2.357},"status":"keep","description":"add proposal-temperature override and test budget 32 at temp 1.0","timestamp":1777503715337,"segment":1,"confidence":11.576312390556494,"asi":{"hypothesis":"greedy sampling uses --temp 0, but DDTree proposal scoring should not necessarily use near-zero temperature; a separate proposal temperature can allocate budget to useful alternatives while exact validation preserves bit-equal output","result":"LLAMA_DDTREE_PROPOSAL_TEMP=1.0 with budget 32 reduced steps from 16 to 14 and improved decode TPS to 10.15 despite higher exact cost per step","next_action_hint":"confirm on repeat and sweep proposal_temp around 0.5/0.75/1.25; if robust, consider making proposal temperature distinct from sampler temperature by default"}}
{"run":82,"commit":"f282526","metric":10.443251,"metrics":{"tps":10.443251,"e2e_tps":1.302932,"spec_sec":24.56,"gen_tokens":32,"steps":14,"committed":33,"step_ms":218.87,"pack_ms":1.11,"draft_ms":140.22,"topk_ms":19.49,"exact_ms":58.02,"exact_decode_ms":0,"acceptance":2.357},"status":"keep","description":"tune DDTree proposal temperature to 0.75","timestamp":1777503819076,"segment":1,"confidence":12.243787036262265,"asi":{"hypothesis":"proposal_temp=0.75 may keep the useful branch diversity from temp 1.0 while weighting top draft candidates more strongly, reducing per-step overhead or improving acceptance stability","result":"proposal_temp=0.75 matched the 14-step/2.36 acceptance gain and improved decode TPS to 10.44 via lower step time than temp 1.0","next_action_hint":"sweep 0.5 and 0.9/1.25, then repeat the best to check noise; validate on a second prompt before hardcoding any default"}}
{"run":83,"commit":"f282526","metric":9.354263,"metrics":{"tps":9.354263,"e2e_tps":1.28123,"spec_sec":24.976,"gen_tokens":32,"steps":15,"committed":34,"step_ms":228.06,"pack_ms":1.09,"draft_ms":149.88,"topk_ms":20.81,"exact_ms":56.24,"exact_decode_ms":0,"acceptance":2.267},"status":"discard","description":"sweep DDTree proposal temperature 0.5","timestamp":1777503920054,"segment":1,"confidence":12.281436942986181,"asi":{"hypothesis":"proposal_temp=0.5 may focus tree budget on higher-confidence draft branches and reduce wasted alternatives versus 0.75/1.0","rollback_reason":"0.5 reduced acceptance relative to 0.75 and needed 15 steps; step time also worsened, so primary TPS dropped below current best","next_action_hint":"proposal_temp around 0.75 remains best; test 0.9 or 0.625 next rather than going lower"}}
{"run":84,"commit":"f282526","metric":10.070113,"metrics":{"tps":10.070113,"e2e_tps":1.299229,"spec_sec":24.63,"gen_tokens":32,"steps":14,"committed":33,"step_ms":226.98,"pack_ms":1.12,"draft_ms":146.35,"topk_ms":20.69,"exact_ms":58.8,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"sweep DDTree proposal temperature 0.9","timestamp":1777504018992,"segment":1,"confidence":12.265451874159854,"asi":{"hypothesis":"proposal_temp=0.9 may keep the 14-step branch-diversity gain of 0.75/1.0 while being less noisy than 0.75","rollback_reason":"0.9 preserved 14 steps and 2.36 acceptance but step time was worse than 0.75, so primary TPS fell below current best","next_action_hint":"0.75 remains the best tested proposal temperature; try 0.625/0.8 or repeat 0.75 for stability"}}
{"run":85,"commit":"f282526","metric":9.341975,"metrics":{"tps":9.341975,"e2e_tps":1.288712,"spec_sec":24.831,"gen_tokens":32,"steps":15,"committed":34,"step_ms":228.36,"pack_ms":1.11,"draft_ms":149.89,"topk_ms":21.18,"exact_ms":56.13,"exact_decode_ms":0,"acceptance":2.267},"status":"discard","description":"sweep DDTree proposal temperature 0.625","timestamp":1777504113549,"segment":1,"confidence":12.249508362405432,"asi":{"hypothesis":"proposal_temp=0.625 may sit between 0.5 and 0.75, preserving more branch diversity than 0.5 while focusing proposals more than 0.75","rollback_reason":"0.625 behaved like 0.5: 15 steps, 2.27 acceptance, and slower step time; primary TPS well below 0.75","next_action_hint":"lower side of temp sweep is done; 0.75 remains best, test 0.8/0.7 or repeat 0.75"}}
{"run":86,"commit":"f282526","metric":9.949568,"metrics":{"tps":9.949568,"e2e_tps":1.292303,"spec_sec":24.762,"gen_tokens":32,"steps":14,"committed":33,"step_ms":229.73,"pack_ms":1.1,"draft_ms":148.29,"topk_ms":21.43,"exact_ms":58.88,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"sweep DDTree proposal temperature 0.8","timestamp":1777504213478,"segment":1,"confidence":12.153903309794075,"asi":{"hypothesis":"proposal_temp=0.8 may be close to the observed 0.75 optimum while possibly more robust than 0.75","rollback_reason":"0.8 kept the 14-step/2.36 acceptance pattern but step time and topk were worse, so primary TPS stayed below 0.75","next_action_hint":"0.75 remains the best tested proposal temperature; test 0.7 or repeat 0.75 for stability"}}
{"run":87,"commit":"c499e6d","metric":10.507099,"metrics":{"tps":10.507099,"e2e_tps":1.308686,"spec_sec":24.452,"gen_tokens":32,"steps":14,"committed":33,"step_ms":217.54,"pack_ms":1.11,"draft_ms":138.33,"topk_ms":19.95,"exact_ms":58.11,"exact_decode_ms":0,"acceptance":2.357},"status":"keep","description":"sweep DDTree proposal temperature 0.7","timestamp":1777504313200,"segment":1,"confidence":12.22183088063815,"asi":{"hypothesis":"proposal_temp=0.7 may be slightly better than 0.75 by keeping the same 14-step branch diversity while weighting top candidates a little more strongly","result":"0.7 preserved the 14-step/2.36 acceptance behavior and improved decode TPS to 10.51 with lower draft/step time than 0.75","next_action_hint":"repeat 0.7 and test 0.68/0.72; validate on additional prompt before making proposal_temp=0.7 a hard default"}}
{"run":88,"commit":"c499e6d","metric":10.013205,"metrics":{"tps":10.013205,"e2e_tps":1.300654,"spec_sec":24.603,"gen_tokens":32,"steps":14,"committed":32,"step_ms":228.27,"pack_ms":1.11,"draft_ms":149.75,"topk_ms":20.67,"exact_ms":56.7,"exact_decode_ms":0,"acceptance":2.286},"status":"discard","description":"sweep DDTree proposal temperature 0.68","timestamp":1777504416257,"segment":1,"confidence":12.743318525446139,"asi":{"hypothesis":"proposal_temp=0.68 may refine the 0.7 optimum by slightly increasing confidence weighting without falling into the 0.625/0.5 lower-acceptance regime","rollback_reason":"0.68 kept 14 steps but committed/acceptance fell and draft/step time worsened, so primary TPS dropped below 0.7","next_action_hint":"0.7 remains better than the lower side; test 0.72 or repeat 0.7 for noise"}}
{"run":89,"commit":"c499e6d","metric":10.111096,"metrics":{"tps":10.111096,"e2e_tps":1.280974,"spec_sec":24.981,"gen_tokens":32,"steps":14,"committed":33,"step_ms":226.06,"pack_ms":1.11,"draft_ms":144.8,"topk_ms":21.34,"exact_ms":58.76,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"sweep DDTree proposal temperature 0.72","timestamp":1777504517855,"segment":1,"confidence":12.766361853364844,"asi":{"hypothesis":"proposal_temp=0.72 may sit close to the 0.7 optimum while preserving 0.75-like acceptance stability","rollback_reason":"0.72 preserved 14 steps and 2.36 acceptance but topk/step time were worse than 0.7; primary TPS below best","next_action_hint":"proposal_temp 0.7 remains best; repeat 0.7 for confirmation or test nearby 0.69/0.71 only if needed"}}
{"run":90,"commit":"c499e6d","metric":9.937888,"metrics":{"tps":9.937888,"e2e_tps":1.292146,"spec_sec":24.765,"gen_tokens":32,"steps":14,"committed":33,"step_ms":230,"pack_ms":1.11,"draft_ms":149.15,"topk_ms":21.08,"exact_ms":58.63,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"repeat DDTree proposal temperature 0.7","timestamp":1777504613299,"segment":1,"confidence":12.802747380091832,"asi":{"hypothesis":"repeat proposal_temp=0.7 to check whether the 10.51 TPS run was stable or mostly noise","rollback_reason":"repeat preserved 14-step/2.36 acceptance but step time regressed to 230 ms, so primary TPS was below the kept best; structural gain is stable but single-run TPS is noisy","next_action_hint":"treat proposal_temp=0.7 as useful for fewer steps but compare future changes against a 9.9-10.5 TPS noise range"}}
{"run":91,"commit":"c499e6d","metric":3.149191,"metrics":{"tps":3.149191,"e2e_tps":1.013588,"spec_sec":31.571,"gen_tokens":32,"steps":14,"committed":33,"step_ms":725.81,"pack_ms":1.16,"draft_ms":149.93,"topk_ms":20.87,"exact_ms":59.92,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"diagnostic batched-vs-exact trace with proposal temp 0.7","timestamp":1777505377073,"segment":1,"confidence":12.319068657292135,"asi":{"hypothesis":"enable batched tree verify trace to measure batched posterior vs exact validation agreement and margin for possible high-confidence exact-skip rule","rollback_reason":"diagnostic trace adds target-tree/snapshot overhead, so primary TPS is expectedly worse and not a runtime optimization","result":"for visible traced tail, batched_exact_same=14 and diff=0 in stats; parsed 3 trace lines all had batched_commit_n equal exact commit_n with min margin 2.12, avg margin 7.62","next_action_hint":"improve trace capture to emit compact aggregate metrics for all steps instead of relying on tailed logs; this run suggests current prompt/temp0.7 has no batched/exact divergence, but broader prompts are needed before trusting batched"}}
{"run":92,"commit":"c499e6d","metric":3.209461,"metrics":{"tps":3.209461,"e2e_tps":1.019303,"spec_sec":31.394,"gen_tokens":32,"steps":14,"committed":33,"step_ms":712.18,"pack_ms":1.16,"draft_ms":152.9,"topk_ms":20.95,"exact_ms":0,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"fast-batched correctness probe at proposal temp 0.7","timestamp":1777505519305,"segment":1,"confidence":11.723331153709331,"asi":{"hypothesis":"if proposal_temp=0.7 eliminates batched/exact divergence on this prompt, fast-batched can skip exact validation and remain bit-equal, clarifying whether exact skip is correctness-safe before optimizing rollback","rollback_reason":"correctness passed, but snapshot+replay fast-batched path is far slower: step=712 ms due snapshot 177.6 ms, target_tree 118.6 ms, replay 53.2 ms; primary TPS much worse","result":"batched path produced bit-equal output with budget32/temp0.7 on this prompt; stats show committed=33, batched_committed=33, max_commit=4, no divergence in final token sequence","next_action_hint":"exact-skip is only useful if paired with no-snapshot fast rollback or another cheap state-commit path; next root-cause work should quantify/compress persist buffers or add aggregate batched/exact margin diagnostics across prompts"}}
{"run":93,"commit":"c499e6d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.672,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.69,"draft_ms":154.36,"topk_ms":14.63,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"diagnose fast rollback persist memory split at budget 14","timestamp":1777505657370,"segment":1,"confidence":11.723331153709331,"asi":{"hypothesis":"quantify DFlash fast-rollback persist allocation into SSM vs conv components to see whether conv F32 is the main compressible memory target","rollback_reason":"diagnostic logging changed code and fast rollback still OOMed before generating tokens, so not a throughput improvement","result":"budget14 planned persist split: ssm=1008.00 MiB, conv=78.75 MiB, total=1086.75 MiB; CUDA allocation failed for the full 1086.75 MiB","next_action_hint":"conv F32 is only about 7.2% of budget14 persist; compressing conv alone cannot make fast rollback fit. The dominant target is SSM persist, already F16 on CUDA, or freeing/defragmenting ~1.1 GiB elsewhere"}}
{"run":94,"commit":"c499e6d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":21.723,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.53,"draft_ms":137.37,"topk_ms":13.7,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"fast rollback fit probe with budget 8 persist","timestamp":1777505801493,"segment":1,"confidence":11.723331153709331,"asi":{"hypothesis":"using a much smaller budget 8 should reduce DFlash fast-rollback persist to about 621 MiB; if it fits, fast-batched plus rollback can reveal whether cheap state commit can offset lower acceptance","rollback_reason":"budget8 persist still OOMed before any token was generated, so no throughput result; snapshot fallback was disabled intentionally to test true fast rollback fit","result":"CUDA allocation failed for 621.00 MiB persist at n_tokens=8; even the small-budget fast rollback path cannot fit in the current 64k/full-target/full-draft memory envelope","next_action_hint":"fast rollback needs either freeing hundreds of MiB elsewhere before persist allocation or changing allocation strategy/lifetime; smaller budget alone is not enough, so investigate target/draft compute buffers or lower n_ctx/offload as controlled diagnostics"}}
{"run":95,"commit":"c499e6d","metric":8.005844,"metrics":{"tps":8.005844,"e2e_tps":1.269589,"spec_sec":25.205,"gen_tokens":32,"steps":18,"committed":33,"step_ms":222.06,"pack_ms":1.08,"draft_ms":132.93,"topk_ms":15.31,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.833},"status":"discard","description":"fast rollback fit probe at 32k context with budget 8","timestamp":1777505918594,"segment":1,"confidence":11.195080202773184,"asi":{"hypothesis":"lowering n_ctx from 64k to 32k may free enough GPU memory for even budget8 fast rollback, revealing whether fast-batched plus cheap state commit can be viable when persist fits","rollback_reason":"32k/budget8 fast rollback fit and remained bit-equal, but acceptance fell to 1.83 over 18 steps and TPS stayed below the current exact-validation best","result":"persist allocated successfully: 621.00 MiB, fast_rollback=18, snapshot_replays=0, exact=0, target_tree=70.61 ms, rollback=0.65 ms, step=222.06 ms, correctness PASS","next_action_hint":"fast rollback itself is cheap when it fits; the remaining costs are target_tree and reduced acceptance at budget8/32k. Test 32k with larger budget if memory allows, or focus on freeing 64k memory for budget32 persist rather than optimizing rollback kernels."}}
{"run":96,"commit":"c499e6d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":0,"gen_tokens":0,"steps":0,"committed":0,"step_ms":0,"pack_ms":0,"draft_ms":0,"topk_ms":0,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"fast rollback fit probe at 32k context with budget 14","timestamp":1777506020282,"segment":1,"confidence":11.195080202773184,"asi":{"hypothesis":"32k context may free enough GPU memory for budget14 fast rollback persist, improving acceptance versus the budget8 fast-batched rollback run while keeping cheap state commit","rollback_reason":"budget14 persist allocated at 32k, but subsequent CUDA graph compute hit out-of-memory before benchmark metrics were emitted, so no throughput result","result":"persist allocation succeeded for 64 layers, 14 tokens, 1086.75 MiB, then CUDA OOM occurred in ggml_backend_cuda_graph_compute during target tree decode","next_action_hint":"32k frees enough memory for budget14 persist allocation but not enough working-memory headroom for compute; test an intermediate smaller budget such as 10 or 12, or reduce graph compute buffer pressure before revisiting budget14"}}
{"run":97,"commit":"c499e6d","metric":6.498729,"metrics":{"tps":6.498729,"e2e_tps":1.223055,"spec_sec":26.164,"gen_tokens":32,"steps":19,"committed":33,"step_ms":259.16,"pack_ms":1.06,"draft_ms":156.53,"topk_ms":16.75,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.737},"status":"discard","description":"fast rollback fit probe at 32k context with budget 12","timestamp":1777506119588,"segment":1,"confidence":11.176576899258043,"asi":{"hypothesis":"32k context with budget12 may be the largest fast-rollback configuration that leaves enough compute headroom, improving acceptance versus budget8 without the budget14 CUDA OOM","rollback_reason":"budget12 fast rollback fit and stayed bit-equal, but acceptance fell to 1.74 over 19 steps and step time rose to 259 ms; primary TPS was far below the budget32 exact-validation best and below the 32k budget8 rollback probe","result":"persist allocated successfully at 931.50 MiB, fast_rollback=19, snapshot_replays=0, exact=0, target_tree=81.96 ms, rollback=0.66 ms, correctness PASS","next_action_hint":"budget12 worsens both acceptance and step time versus budget8 on this prompt; do not pursue 32k rollback budget sweep as an optimization. The useful finding is that rollback is cheap when persist fits; focus on freeing 64k memory or reducing target_tree cost."}}
{"run":98,"commit":"c499e6d","metric":7.723089,"metrics":{"tps":7.723089,"e2e_tps":1.206091,"spec_sec":26.532,"gen_tokens":32,"steps":18,"committed":33,"step_ms":230.19,"pack_ms":1.11,"draft_ms":137.84,"topk_ms":15.24,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.833},"status":"discard","description":"64k fast rollback fit probe with smaller batch buffers and budget 8","timestamp":1777506225210,"segment":1,"confidence":11.158134659584107,"asi":{"hypothesis":"reducing n_batch/n_ubatch from 512 to 256 may free enough 64k GPU working memory for budget8 fast rollback persist while preserving the 64k prompt/proposal behavior better than lowering n_ctx to 32k","rollback_reason":"fast rollback fit and correctness passed, but budget8 acceptance stayed low at 1.83 over 18 steps and TPS remained below the budget32 exact-validation best","result":"64k with n_batch=256,n_ubatch=256 allocated 621.00 MiB persist, fast_rollback=18, snapshot_replays=0, exact=0, target_tree=73.86 ms, rollback=0.62 ms, correctness PASS","next_action_hint":"smaller batch buffers solve the 64k budget8 persist fit, but budget8 acceptance is too low; test whether n_batch=256 allows budget14 or higher persist, otherwise freeing memory alone at tiny budget is not enough"}}
{"run":99,"commit":"c499e6d","metric":7.011148,"metrics":{"tps":7.011148,"e2e_tps":1.201021,"spec_sec":26.644,"gen_tokens":32,"steps":17,"committed":33,"step_ms":268.48,"pack_ms":1.09,"draft_ms":160.71,"topk_ms":16.82,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"64k fast rollback fit probe with smaller batch buffers and budget 14","timestamp":1777506326499,"segment":1,"confidence":10.999616549456363,"asi":{"hypothesis":"with n_batch/n_ubatch reduced to 256, 64k may have enough memory for budget14 fast rollback persist, improving acceptance over budget8 while keeping cheap rollback state commits","rollback_reason":"budget14 fast rollback fit and stayed bit-equal, but step time rose to 268 ms and acceptance only improved to 1.94, so primary TPS remained below both budget8 rollback and the budget32 exact-validation best","result":"64k n_batch=256,n_ubatch=256 allocated 1086.75 MiB persist, fast_rollback=17, snapshot_replays=0, exact=0, target_tree=86.66 ms, rollback=0.64 ms, correctness PASS","next_action_hint":"n_batch reduction frees enough memory for budget14, but target_tree+draft cost dominate and acceptance remains below the budget32 exact path; test whether budget22/32 fit with n_batch=256 only as a memory map, otherwise stop fast-rollback budget sweep and investigate target_tree cost or GPU target_feat ring."}}
{"run":100,"commit":"c499e6d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":22.457,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":3.57,"draft_ms":157.23,"topk_ms":20.94,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"64k fast rollback fit probe with smaller batch buffers and budget 22","timestamp":1777506423953,"segment":1,"confidence":10.999616549456363,"asi":{"hypothesis":"with n_batch/n_ubatch reduced to 256, 64k may have enough memory for budget22 fast rollback persist, restoring more acceptance than budget8/14 while avoiding exact validation","rollback_reason":"budget22 persist still OOMed before generating tokens, so no throughput result; snapshot fallback was disabled intentionally to test true fast rollback fit","result":"CUDA allocation failed for 1707.75 MiB persist at n_tokens=22 even with n_batch=256,n_ubatch=256; budget14 is the largest tested 64k rollback configuration that fits, but it is too slow","next_action_hint":"do not pursue higher budget fast rollback under current 64k/full-draft memory envelope. Fast rollback needs either a smaller persist representation or major memory freeing; shift to target_tree cost reduction or GPU-resident target_feat ring diagnostics."}}
{"run":101,"commit":"c499e6d","metric":0,"metrics":{"tps":0,"e2e_tps":0,"spec_sec":26.823,"gen_tokens":0,"steps":1,"committed":0,"step_ms":0,"pack_ms":1.57,"draft_ms":153.13,"topk_ms":21.01,"exact_ms":0,"exact_decode_ms":0,"acceptance":0},"status":"crash","description":"64k fast rollback fit probe with n_batch 128 and budget 22","timestamp":1777506525928,"segment":1,"confidence":10.999616549456363,"asi":{"hypothesis":"reducing n_batch/n_ubatch further from 256 to 128 may free enough 64k GPU memory for budget22 fast rollback persist, restoring acceptance while avoiding exact validation","rollback_reason":"budget22 persist still OOMed before generating tokens even with n_batch=128; snapshot fallback was disabled intentionally to test true fast rollback fit","result":"CUDA allocation failed for 1707.75 MiB persist at n_tokens=22; reducing n_batch below 256 did not free enough additional memory, while prompt_ingests doubled to 160","next_action_hint":"stop trying to fit budget22/32 fast rollback via n_batch reduction. Need different persist representation, moving buffers off GPU, or target_tree/GPU target_feat root-cause work."}}
{"run":102,"commit":"c499e6d","metric":3.404755,"metrics":{"tps":3.404755,"e2e_tps":1.040312,"spec_sec":30.76,"gen_tokens":32,"steps":14,"committed":33,"step_ms":671.33,"pack_ms":1.15,"draft_ms":144.48,"topk_ms":20.62,"exact_ms":59.5,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"aggregate batched-vs-exact margin diagnostics at proposal temp 0.7","timestamp":1777506711000,"segment":1,"confidence":10.845539326886065,"asi":{"hypothesis":"add compact aggregate margin metrics for all diagnostic batched tree steps to evaluate whether a high-confidence exact-skip rule could be safe without relying on truncated per-node trace logs","rollback_reason":"diagnostic target-tree verification and logging are expectedly much slower than the runtime exact-validation path, so primary TPS is below best and the code is not a production optimization","result":"on the current prompt with budget32/temp0.7, batched_exact_same=14 and diff=0; aggregate margin steps=14, batched_min_avg=9.087, batched_min_min=0.895, ge1 same=13/13, ge2 same=12/12, ge5 same=9/9","next_action_hint":"current prompt supports a confidence-gated exact skip with thresholds >=1 or >=2, but this is not enough to ship; validate aggregate margins on additional prompts before trusting batched posterior, and pair any exact skip with cheap state commit because snapshot+replay is slower."}}
{"run":103,"commit":"c499e6d","metric":6.832497,"metrics":{"tps":6.832497,"e2e_tps":1.205636,"spec_sec":26.542,"gen_tokens":32,"steps":17,"committed":33,"step_ms":275.5,"pack_ms":1.1,"draft_ms":157.54,"topk_ms":20.23,"exact_ms":0,"exact_decode_ms":0,"acceptance":1.941},"status":"discard","description":"64k fast rollback fit probe with smaller batch buffers and budget 16","timestamp":1777506853395,"segment":1,"confidence":10.715120218615038,"asi":{"hypothesis":"budget16 may be a 64k fast-rollback middle point that still fits with n_batch/n_ubatch=256 while improving acceptance over budget8/14 enough to offset target_tree cost","rollback_reason":"budget16 fast rollback fit and stayed bit-equal, but acceptance remained 1.94 like budget14 while step time worsened to 275.5 ms, so primary TPS stayed far below the budget32 exact-validation best","result":"64k n_batch=256,n_ubatch=256 allocated 1242.00 MiB persist, fast_rollback=17, snapshot_replays=0, exact=0, target_tree=93.03 ms, rollback=0.68 ms, correctness PASS","next_action_hint":"fast rollback parameter sweep is exhausted: budget8/14/16 fit but are slow, budget22 OOMs. Move to target_tree cost reduction, broader batched/exact confidence validation, or GPU-resident target_feat ring instead of more budget tuning."}}
{"run":104,"commit":"c499e6d","metric":3.414521,"metrics":{"tps":3.414521,"e2e_tps":1.03795,"spec_sec":30.83,"gen_tokens":32,"steps":14,"committed":33,"step_ms":669.41,"pack_ms":1.16,"draft_ms":146.87,"topk_ms":20.93,"exact_ms":60.27,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"target-only chain decode timing diagnostic attempt","timestamp":1777507043307,"segment":1,"confidence":10.587800455864077,"asi":{"hypothesis":"instrument the chain reference path to quantify target-only one-token decode time and compare it with DDTree exact validation, clarifying whether the target-only reference mismatch comes from target decode overhead","rollback_reason":"diagnostic output was not surfaced because autoresearch.sh only tails the last 120 lines, and a preserved TRACE env pass-through accidentally enabled expensive target-tree tracing for every run; primary TPS is therefore not comparable","result":"the run still passed correctness but showed trace overhead: target_tree=118.29 ms and snapshot=150.34 ms in the exact path; chain timing detail needs a rerun after fixing TRACE pass-through/output capture","next_action_hint":"fix autoresearch.sh so empty LLAMA_DDTREE_TRACE does not enable tracing, then rerun the chain timing diagnostic with enough output to capture chain timing detail"}}
{"run":105,"commit":"9fbce93","metric":11.924636,"metrics":{"tps":11.924636,"e2e_tps":1.328573,"spec_sec":24.086,"gen_tokens":32,"steps":14,"committed":33,"step_ms":191.68,"pack_ms":1.1,"draft_ms":114.78,"topk_ms":17.91,"exact_ms":57.86,"exact_decode_ms":0,"acceptance":2.357},"status":"keep","description":"fix empty trace pass-through and add chain timing diagnostic hook","timestamp":1777507150730,"segment":1,"confidence":13.950437243906348,"asi":{"hypothesis":"the preserved autoresearch trace env pass-through was accidentally enabling target-tree diagnostics even when LLAMA_DDTREE_TRACE was empty; fixing it should restore normal exact-validation timing and allow a target-only chain timing diagnostic hook","result":"normal exact-validation path restored: target_tree=0, snapshot=0, step=191.68 ms, draft=114.78 ms, exact=57.86 ms, acceptance=2.36, tps=11.92; this is a measurement/harness fix rather than a product-code speedup","next_action_hint":"rerun once to confirm the 11.9 TPS result is not noise, and increase autoresearch output capture further if chain timing detail is still needed"}}
{"run":106,"commit":"9fbce93","metric":10.063906,"metrics":{"tps":10.063906,"e2e_tps":1.307083,"spec_sec":24.482,"gen_tokens":32,"steps":14,"committed":33,"step_ms":227.12,"pack_ms":1.11,"draft_ms":146.94,"topk_ms":20.58,"exact_ms":58.45,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"repeat normal exact-validation path after trace pass-through fix","timestamp":1777507233994,"segment":1,"confidence":13.654565431988555,"asi":{"hypothesis":"repeat the restored no-trace exact-validation path to determine whether the 11.92 TPS run was a real speedup or timing noise","rollback_reason":"repeat preserved the 14-step/2.36 acceptance behavior and no target_tree overhead, but step time returned to 227 ms and primary TPS fell below the kept 11.92 run","result":"target_tree=0 and snapshot=0 confirm the trace pass-through fix works; the 11.92 TPS run was mostly draft/step-time noise, while normal performance remains around 10.0 TPS","next_action_hint":"continue comparing future changes against a noisy 10.0-11.9 TPS range; if chain timing detail is still needed, make autoresearch.sh print the chain timing lines explicitly instead of relying on tail length."}}
{"run":107,"commit":"9fbce93","metric":9.951734,"metrics":{"tps":9.951734,"e2e_tps":1.299756,"spec_sec":24.62,"gen_tokens":32,"steps":14,"committed":33,"step_ms":229.68,"pack_ms":1.12,"draft_ms":149.57,"topk_ms":20.36,"exact_ms":58.6,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"surface target-only chain decode timing diagnostic","timestamp":1777507363548,"segment":1,"confidence":13.340332316400888,"asi":{"hypothesis":"print the chain reference timing lines from the full benchmark log so we can compare target-only one-token decode against DDTree exact validation and identify whether target decode itself is anomalously slow","rollback_reason":"this was a diagnostic harness output change and primary TPS stayed below the kept best; no production code speedup","result":"target-only chain after prompt has decode_avg=24.79 ms over 32 tokens, while DDTree exact validation is 58.60 ms per speculative step plus draft/topk; the target-only server reference gap is therefore not explained by base one-token target decode alone","next_action_hint":"investigate why DDTree exact validation costs ~58 ms/step versus target-only 1-token decode ~25 ms, likely hidden capture, seq_rm/cache state, or validation loop overhead; profile exact validation internals before more proposal tuning"}}
{"run":108,"commit":"9fbce93","metric":10.245246,"metrics":{"tps":10.245246,"e2e_tps":1.309436,"spec_sec":24.438,"gen_tokens":32,"steps":14,"committed":33,"step_ms":223.1,"pack_ms":1.11,"draft_ms":143.19,"topk_ms":20.11,"exact_ms":58.66,"exact_decode_ms":58.19,"acceptance":2.357},"status":"discard","description":"profile exact validation decode/sample timing","timestamp":1777507489027,"segment":1,"confidence":12.942229525616327,"asi":{"hypothesis":"instrument exact validation internals to determine whether the ~58 ms exact cost comes from llama_decode, logits sampling, advance callbacks, or driver overhead","rollback_reason":"diagnostic timing output only; primary TPS stayed below the kept best and there is no product-code optimization in this change","result":"exact validation is almost entirely target llama_decode: exact=58.66 ms/step, exact_decode=58.19 ms/step, exact_sample=0.41 ms/step, exact_nodes=33 over 14 steps; target-only chain decode remains 24.69 ms/token","next_action_hint":"focus on why exact validation llama_decode is ~2.35x slower per token than target-only chain decode: hidden capture enabled during spec, seq_rm/KV state mutations, or context state after draft/tree operations. Run a controlled chain-with-hidden-capture timing diagnostic next."}}
{"run":109,"commit":"9fbce93","metric":10.373578,"metrics":{"tps":10.373578,"e2e_tps":1.315735,"spec_sec":24.321,"gen_tokens":32,"steps":14,"committed":33,"step_ms":220.34,"pack_ms":1.12,"draft_ms":139.62,"topk_ms":20.94,"exact_ms":58.62,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"chain decode timing with hidden capture enabled","timestamp":1777507637568,"segment":1,"confidence":12.882552326173203,"asi":{"hypothesis":"if hidden capture is the reason DDTree exact validation llama_decode is ~2.35x slower than target-only chain decode, enabling capture_hidden on the chain reference should raise chain decode_avg toward ~58 ms/token","rollback_reason":"diagnostic-only harness/env pass-through change; primary TPS did not improve over the kept best","result":"with LLAMA_DDTREE_CHAIN_CAPTURE=1, chain decode_avg remained 24.74 ms/token while DDTree exact stayed 58.62 ms/step; hidden capture alone does not explain the exact-validation decode slowdown","next_action_hint":"next isolate seq_rm/KV state mutation or repeated position rollback effects: run target-only chain with seq_rm before each decode, or instrument exact validation to measure llama_memory_seq_rm and per-node decode depth costs."}}
{"run":110,"commit":"9fbce93","metric":10.039594,"metrics":{"tps":10.039594,"e2e_tps":1.291312,"spec_sec":24.781,"gen_tokens":32,"steps":14,"committed":33,"step_ms":227.67,"pack_ms":1.11,"draft_ms":147.57,"topk_ms":20.34,"exact_ms":58.61,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"chain decode timing with hidden capture and seq_rm controls","timestamp":1777507811343,"segment":1,"confidence":12.847363213337257,"asi":{"hypothesis":"if DDTree exact validation is slower because of hidden capture or the seq_rm call before validation, then target-only chain decode with capture_hidden plus seq_rm before every decode should approach the ~58 ms exact-validation cost","rollback_reason":"diagnostic-only harness changes; primary TPS stayed below the kept best and no production optimization was introduced","result":"chain with capture+seq_rm still decoded at 24.81 ms/token; seq_rm itself averaged only 0.026 ms. DDTree exact remained 58.61 ms/step, so neither hidden capture nor a no-op seq_rm explains the slowdown","next_action_hint":"isolate context-state effects specific to DDTree exact validation: repeated decode of root/current positions after previous speculative commits, recurrent/SSM state mutation, or graph shape/reuse differences. Next useful diagnostic is per-depth exact decode timing or chain replay pattern that decodes root+accepted path chunks like validation."}}
{"run":111,"commit":"9fbce93","metric":10.079439,"metrics":{"tps":10.079439,"e2e_tps":1.297911,"spec_sec":24.655,"gen_tokens":32,"steps":14,"committed":33,"step_ms":226.77,"pack_ms":1.11,"draft_ms":146.48,"topk_ms":20.54,"exact_ms":58.6,"exact_decode_ms":58.14,"acceptance":2.357},"status":"discard","description":"normalize exact validation decode cost per node","timestamp":1777507941061,"segment":1,"confidence":12.752562835954159,"asi":{"hypothesis":"the apparent ~58 ms exact-validation cost may be per speculative step, not per target token; logging exact_nodes and exact_decode per node should clarify whether exact llama_decode is actually slower than target-only chain decode","rollback_reason":"diagnostic-only harness logging; primary TPS stayed below the kept best and no runtime optimization was introduced","result":"exact_nodes=33 over 14 steps; exact_decode=58.14 ms/step but exact_node=24.66 ms/token, matching target-only chain decode_avg=24.76 ms/token. Exact validation is not slower per token; it costs about accepted_nodes_per_step target decodes.","next_action_hint":"stop treating exact validation as a per-token slowdown. The remaining throughput gap is structural: each DDTree step pays draft/topk plus ~2.36 target decodes. Next focus on either trusting batched posterior with cheap state commit, reducing target decodes per step, or lowering draft/topk cost."}}
{"run":112,"commit":"9fbce93","metric":10.473398,"metrics":{"tps":10.473398,"e2e_tps":1.308312,"spec_sec":24.459,"gen_tokens":32,"steps":14,"committed":33,"step_ms":218.24,"pack_ms":0.95,"draft_ms":139.62,"topk_ms":19.74,"exact_ms":57.9,"exact_decode_ms":0,"acceptance":2.357},"status":"discard","description":"test smaller target feature window 112 with proposal temp 0.7","timestamp":1777508043255,"segment":1,"confidence":12.651180373150947,"asi":{"hypothesis":"with proposal_temp=0.7 preserving the 14-step acceptance pattern, reducing target_feat_ctx from 128 to 112 may lower draft/pack cost without losing proposal quality","rollback_reason":"target_feat_ctx=112 preserved 14 steps and 2.36 acceptance and reduced pack/draft versus typical 128 runs, but primary TPS did not beat the kept best and remains within the noisy 10.0-11.9 range","result":"112-window produced tps=10.47, step=218.24 ms, draft=139.62 ms, pack=0.95 ms, acceptance=2.36; proposal_temp=0.7 appears to recover the acceptance loss previously seen at 112 without a clear primary improvement","next_action_hint":"test 96 or 104 only if looking for more draft-cost reduction, but compare against noise; avoid declaring smaller windows best until repeated and validated on broader prompts"}}
{"run":113,"commit":"9fbce93","metric":9.938876,"metrics":{"tps":9.938876,"e2e_tps":1.298174,"spec_sec":24.65,"gen_tokens":32,"steps":16,"committed":33,"step_ms":201.23,"pack_ms":0.88,"draft_ms":131.18,"topk_ms":18.74,"exact_ms":50.38,"exact_decode_ms":0,"acceptance":2.062},"status":"discard","description":"test smaller target feature window 104 with proposal temp 0.7","timestamp":1777508138445,"segment":1,"confidence":13.074597480445423,"asi":{"hypothesis":"with proposal_temp=0.7, target_feat_ctx=104 may further reduce draft/pack cost while still preserving enough proposal quality to beat the 128-window exact-validation path","rollback_reason":"104 reduced draft/pack and per-step time, but lost the 14-step acceptance pattern: steps rose to 16 and acceptance fell to 2.06, so primary TPS stayed below the current best","result":"target_feat_ctx=104 produced step=201.23 ms, draft=131.18 ms, pack=0.88 ms, but required 16 steps; smaller windows below 112 start trading away the structural acceptance gain","next_action_hint":"avoid shrinking target_feat_ctx below 112 for this prompt/temp unless validating a latency-focused variant; next try broader-prompt batched/exact confidence validation or target_tree/state-commit work rather than more small window tuning"}}
{"type":"config","name":"Optimize DFlash DDTree decode TPS on Castle - Phase 2: Batched posterior + fast commit","metricName":"tps","metricUnit":"","bestDirection":"higher"}
{"run":114,"commit":"166b674","metric":9.411626,"metrics":{},"status":"keep","description":"Phase 2 baseline: proposal_temp=0.7, budget=32, target_feat_ctx=128, exact-validation path on real_rendered_prompt","timestamp":1777537489249,"segment":2,"confidence":null,"asi":{"hypothesis":"establish new segment baseline with current best config before pursuing batched posterior validation and fast commit optimizations","benchmark":"./autoresearch.sh on Castle; gen=32; prompt=/tmp/real_rendered_prompt.txt; LLAMA_DDTREE_PROPOSAL_TEMP=0.7; LLAMA_DDTREE_TARGET_FEAT_CTX=128","note":"steps=15 vs previous segment best 14-step runs; within noise band 9.4-10.5 TPS"}}
{"run":115,"commit":"9fbce93","metric":7.28014,"metrics":{},"status":"discard","description":"fast-batched + fast-rollback with budget 10 at 64k context","timestamp":1777541038238,"segment":2,"confidence":null,"asi":{"hypothesis":"test whether fast-batched path with small budget 10 can achieve acceptable TPS without exact validation","note":"fast rollback fits at budget10 with n_batch=256; acceptance=1.94, step=258ms, TPS=7.28 vs baseline 9.41","next_action_hint":"budget10 fast-batched is worse than exact path; try smaller budgets or combine with other optimizations"}}
{"run":116,"commit":"9fbce93","metric":7.136072,"metrics":{},"status":"discard","description":"fast-batched + fast-rollback with budget 14 at 64k context","timestamp":1777541046222,"segment":2,"confidence":null,"asi":{"hypothesis":"test whether budget 14 fast-batched improves over budget 10 with better acceptance","note":"budget 14 step time increased to 264ms but acceptance stayed 1.94; TPS=7.14 worse than budget 10","next_action_hint":"larger budgets increase target_tree cost without acceptance gain in fast-batched mode; smaller budgets may be better"}}
{"run":117,"commit":"9fbce93","metric":7.851335,"metrics":{},"status":"discard","description":"fast-batched + fast-rollback with budget 8 at 64k context","timestamp":1777541054565,"segment":2,"confidence":null,"asi":{"hypothesis":"test whether budget 8 fast-batched achieves best TPS among small-budget fast-rollback fits","next_action_hint":"budget 8 is the best fast-batched config so far (7.85 TPS) but still below exact path; target_tree decode dominates fast-batched cost","note":"budget 8 step=226ms, acceptance=1.83, draft=135ms; fast-batched path consistently slower than exact validation for this implementation"}}
{"run":118,"commit":"ade211a","metric":10.195434,"metrics":{"e2e_tps":1.306336,"spec_sec":24.496,"gen_tokens":32,"steps":14,"committed":33,"step_ms":224.19,"pack_ms":1.16,"draft_ms":143.91,"topk_ms":20.75,"exact_ms":58.32,"acceptance":2.357},"status":"keep","description":"test DDTree top_k=4 with proposal temp 0.7 exact-validation path","timestamp":1777543025604,"segment":2,"confidence":1.0958318828179303,"asi":{"benchmark":"./autoresearch.sh; prompt=/tmp/real_rendered_prompt.txt; LLAMA_DDTREE_PROPOSAL_TEMP=0.7; AUTORESEARCH_BUDGET=32; LLAMA_DDTREE_TOP_K=4","hypothesis":"reducing DDTree top-k cardinality from default 8 to 4 may lower CPU top-k scan cost without losing acceptance on this prompt","next_action_hint":"repeat K=4 and test K=2 to see if smaller K continues to help or hurts acceptance; if stable, consider defaulting to K=4","note":"first K=4 run gave 10.20 TPS, repeat gave 10.03; both above 9.41 baseline but within historical 9.4-10.5 noise band; draft/step time slightly lower than baseline"}}
{"run":119,"commit":"e385d50","metric":10.147005,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":145.55,"e2e_tps":1.302932,"exact_ms":58.27,"gen_tokens":32,"pack_ms":0.94,"spec_sec":24.56,"step_ms":225.26,"steps":14,"topk_ms":20.47},"status":"keep","description":"test target_feat_ctx=112 with top_k=4 and proposal_temp=0.7 exact path","timestamp":1777545728081,"segment":2,"confidence":0.550668850678441,"asi":{"hypothesis":"smaller target feature window 112 may reduce draft compute without losing acceptance versus 128","next_action_hint":"test ctx=96 or 104 to find the lower bound; if none beat 128, keep 128 as default","note":"ctx=112 produced 10.15 TPS, step=225ms, draft=145ms, acceptance=2.36; within noise of ctx=128 best"}}
{"run":120,"commit":"ff511ad","metric":9.892726,"metrics":{"acceptance":2.429,"committed":34,"draft_ms":147.88,"e2e_tps":0.951446,"exact_ms":61.21,"gen_tokens":32,"pack_ms":1.11,"spec_sec":33.633,"step_ms":231.05,"steps":14,"topk_ms":20.82},"status":"keep","description":"exact path with n_batch=64 to validate per-layer persist allocation does not regress baseline","timestamp":1777546971003,"segment":2,"confidence":1,"asi":{"hypothesis":"validate that per-layer persist allocation + n_batch=64 does not break exact path correctness or TPS","next_action_hint":"per-layer allocation is committed and safe; continue exploring fast-batched optimization or server integration","note":"n_batch=64 exact path achieved 9.89 TPS, slightly below n_batch=512 best (10.15) but within noise; per-layer allocation code is working"}}
{"run":121,"commit":"ff511ad","metric":10.188617,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":143.93,"e2e_tps":1.307029,"exact_ms":58.34,"gen_tokens":32,"pack_ms":1.11,"spec_sec":24.483,"step_ms":224.34,"steps":14,"topk_ms":20.92},"status":"discard","description":"exact path budget 40 with top_k=4 and proposal_temp=0.7 to test acceptance saturation beyond budget 32","timestamp":1777547541311,"segment":2,"confidence":1.451900946467489,"asi":{"hypothesis":"budget 40 provides more tree nodes than budget 32, potentially increasing acceptance per step enough to reduce total steps and improve overall TPS","rollback_reason":"budget 40 produced identical acceptance (2.357), steps (14), and committed (33) as budget 32, with nearly identical step time (~224ms); extra budget nodes do not improve proposal quality on this prompt","next_action_hint":"acceptance is saturated at ~2.36 for this prompt with budget >=32; try budget 28 or 30 to see if lower budget achieves same acceptance with less overhead, or switch to cross-prompt validation or server integration testing"}}
{"run":122,"commit":"974eb18","metric":11.808554,"metrics":{"acceptance":2.267,"committed":34,"draft_ms":106.3,"e2e_tps":1.32714,"exact_ms":55.5,"gen_tokens":32,"pack_ms":1.06,"spec_sec":24.112,"step_ms":180.66,"steps":15,"topk_ms":17.77},"status":"keep","description":"exact path budget 28 with top_k=4 and proposal_temp=0.7 — large draft speedup vs budget 32","timestamp":1777547640327,"segment":2,"confidence":4.982182498441078,"asi":{"hypothesis":"budget 28 may reduce draft tree-compute overhead more than it hurts acceptance, yielding better TPS than budget 32 despite slightly lower per-step acceptance","next_action_hint":"repeat budget 28 immediately to validate whether the 106ms draft time and 11.81 TPS are stable or noise; if repeatable, this is a major finding","note":"budget 28 step time dropped to 180.66ms (from ~224ms at budget 32), driven by draft_ms falling to 106.3ms (from ~144ms); acceptance slightly lower at 2.267 vs 2.357 but more than offset by per-step speedup"}}
{"run":123,"commit":"974eb18","metric":10.144721,"metrics":{"acceptance":2.267,"committed":34,"draft_ms":133.06,"e2e_tps":1.307831,"exact_ms":56.01,"gen_tokens":32,"pack_ms":1.07,"spec_sec":24.468,"step_ms":210.29,"steps":15,"topk_ms":20.12},"status":"discard","description":"repeat budget 28 to validate the 11.81 TPS result","timestamp":1777547746753,"segment":2,"confidence":6.1161100677716975,"asi":{"hypothesis":"repeat budget 28 to check whether the 11.81 TPS run was stable or noise","next_action_hint":"budget 28 repeat at 10.14 TPS is comparable to budget 32 (10.20 TPS); try budget 30 as the intermediate sweet spot, or investigate why draft time varies so widely (106-144ms)","note":"repeat budget 28 draft_ms=133.06ms, step_ms=210.29ms, TPS=10.14 — much closer to budget 32 than the first run's 106ms/180ms/11.81; first run was likely an outlier","rollback_reason":"10.14 TPS is slightly below the kept budget 32 best of 10.20 TPS; budget 28 is not clearly better"}}
{"run":124,"commit":"ff511ad","metric":10.068782,"metrics":{"acceptance":2.286,"committed":32,"draft_ms":148.42,"e2e_tps":1.304472,"exact_ms":56.42,"gen_tokens":32,"pack_ms":1.09,"spec_sec":24.531,"step_ms":227.01,"steps":14,"topk_ms":21.04},"status":"discard","description":"exact path budget 30 with top_k=4 and proposal_temp=0.7 — intermediate sweep between 28 and 32","timestamp":1777547834290,"segment":2,"confidence":13.614577179988123,"asi":{"hypothesis":"budget 30 may be the sweet spot between budget 28 and 32, preserving acceptance while reducing overhead","rollback_reason":"budget 30 produced lower acceptance (2.286 vs 2.357), higher draft time (148ms vs 144ms), and lower TPS (10.07 vs 10.20) than budget 32; budget 32 remains the best exact-path configuration","next_action_hint":"budget 32 is the exact-path sweet spot; validate on a different prompt to check for overfitting, or try top_k=6, or explore reducing exact validation cost per step"}}
{"run":125,"commit":"ff511ad","metric":14.684288,"metrics":{"acceptance":2.4,"committed":12,"draft_ms":84.62,"e2e_tps":11.472275,"exact_ms":57.61,"gen_tokens":12,"pack_ms":0.37,"spec_sec":1.046,"step_ms":163.44,"steps":5,"topk_ms":20.8},"status":"discard","description":"cross-prompt validation on qwen_rendered_prompt.txt with best config — only 12 tokens generated, not comparable to 32-token benchmark","timestamp":1777547880051,"segment":2,"confidence":5.272893061768601,"asi":{"hypothesis":"validate best config (budget 32, top_k=4, proposal_temp=0.7) on a different prompt to check for overfitting","next_action_hint":"this prompt only generated 12 tokens (EOS early), making it incomparable to the 32-token benchmark; try a different prompt that generates closer to 32 tokens, such as task761 or task0","note":"config works correctly on different prompt (bit-equal PASS) with acceptance=2.40, but short generation makes TPS incomparable"}}
{"run":126,"commit":"ff511ad","metric":7.524101,"metrics":{"acceptance":1.65,"committed":33,"draft_ms":149.57,"e2e_tps":1.181422,"exact_ms":41.2,"gen_tokens":32,"pack_ms":1.03,"spec_sec":27.086,"step_ms":212.65,"steps":20,"topk_ms":20.82},"status":"discard","description":"cross-prompt validation on task761 (21k tokens) with best config — acceptance drops to 1.65, TPS falls to 7.52","timestamp":1777547973644,"segment":2,"confidence":3.647426181911143,"asi":{"hypothesis":"validate best config on a different prompt to check for overfitting","next_action_hint":"acceptance varies significantly by prompt (1.65 vs 2.36); test whether higher budget or top_k=6 improves harder prompts without hurting the benchmark prompt","note":"task761 generated 32 tokens in 20 steps (vs 14 on real_rendered), acceptance 1.65; draft model effectiveness varies by prompt; config is correct (bit-equal PASS) but slower on this prompt","rollback_reason":"7.52 TPS is below baseline on this prompt, but this is a cross-validation run rather than a benchmark regression; the benchmark prompt remains the optimization target"}}
{"run":127,"commit":"ff511ad","metric":9.903871,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":149.32,"e2e_tps":1.293766,"exact_ms":58.77,"gen_tokens":32,"pack_ms":1.11,"spec_sec":24.734,"step_ms":230.79,"steps":14,"topk_ms":21.56},"status":"discard","description":"exact path top_k=2 with budget 32 and proposal_temp=0.7 — acceptance same as top_k=4 but slightly slower","timestamp":1777548247599,"segment":2,"confidence":6.1161100677716975,"asi":{"hypothesis":"top_k=2 may reduce topk overhead while maintaining acceptance if the extra K=4 candidates are unused on this prompt","next_action_hint":"top_k=2 acceptance is identical to top_k=4 on this prompt (2.357), but draft/topk noise makes it slightly slower; try n_ctx=32k to see if reduced KV cache pressure helps target decode, or test top_k=4 on task761 to check cross-prompt generalization","rollback_reason":"9.90 TPS is below the kept top_k=4 best of 10.20 TPS; top_k=2 is not better on the benchmark prompt","note":"acceptance unchanged at 2.357, confirming that extra K=4 candidates do not improve acceptance on this prompt; draft time 149ms vs 144ms is within noise"}}
{"run":128,"commit":"ff511ad","metric":10.212288,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":143.97,"e2e_tps":1.301236,"exact_ms":58.07,"gen_tokens":32,"pack_ms":1.09,"spec_sec":24.592,"step_ms":223.82,"steps":14,"topk_ms":20.66},"status":"discard","description":"exact path with n_ctx=32768 to test if reduced KV cache allocation improves TPS","timestamp":1777548345195,"segment":2,"confidence":13.614577179988123,"asi":{"hypothesis":"n_ctx=32768 reduces KV cache allocation overhead compared to 65536, potentially improving target decode speed","next_action_hint":"n_ctx has no meaningful effect on exact-path TPS; try draft GPU layers 5 or explore exact-validation batching/parallelization","note":"n_ctx=32k produced 10.21 TPS, essentially identical to 64k (10.20); KV cache pressure is not the bottleneck for this prompt length (20k tokens)","rollback_reason":"10.21 TPS is indistinguishable from 10.20 best; no improvement from halving n_ctx"}}
{"run":129,"commit":"ff511ad","metric":8.558163,"metrics":{"acceptance":2.429,"committed":34,"draft_ms":187.64,"e2e_tps":1.283028,"exact_ms":59.93,"gen_tokens":32,"pack_ms":1.1,"spec_sec":24.941,"step_ms":267.08,"steps":14,"topk_ms":18.36},"status":"discard","description":"exact path with draft GPU layers 5 — one layer off GPU hurts draft time significantly","timestamp":1777548448213,"segment":2,"confidence":5.987365455085925,"asi":{"hypothesis":"draft GPU layers 5 may reduce GPU memory contention or improve CPU-GPU balance","next_action_hint":"ngld6 is optimal for exact path; do not reduce draft offload further. Next explore exact-validation batching/parallelization or target decode call overhead reduction.","note":"draft_ms jumped to 187.64ms from ~144ms, step_ms to 267ms; moving draft layers off GPU hurts more than any acceptance gain","rollback_reason":"8.56 TPS is far below the 10.20 best; draft GPU offload must stay at 6 for exact path performance"}}
{"run":130,"commit":"974eb18","metric":9.884597,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":150.8,"e2e_tps":1.298069,"exact_ms":58.39,"gen_tokens":32,"pack_ms":1.11,"spec_sec":24.652,"step_ms":231.24,"steps":14,"topk_ms":20.91},"status":"discard","description":"exact path with chain_seed=0 (pure best-first) and optimized params — chain seed still helps","timestamp":1777548855529,"segment":2,"confidence":7.771711676074962,"asi":{"hypothesis":"with top_k=4 and proposal_temp=0.7, pure best-first might produce a better tree than chain seed","next_action_hint":"chain seed remains beneficial; do not disable it. Next try gen=64 diagnostic or explore exact-validation batching code optimization.","note":"chain_seed=0 produced 9.88 TPS vs 10.20 with default chain seed; draft_ms=150.8 vs ~144ms; chain seed improves tree quality enough to offset any overhead","rollback_reason":"9.88 TPS below best; chain seed default is correct"}}
{"run":131,"commit":"974eb18","metric":9.720872,"metrics":{"acceptance":2.1,"committed":42,"draft_ms":143.17,"e2e_tps":1.631702,"exact_ms":51.79,"gen_tokens":42,"pack_ms":1.03,"spec_sec":25.74,"step_ms":216.03,"steps":20,"topk_ms":20},"status":"discard","description":"diagnostic run with gen=64 to check TPS over longer generation","timestamp":1777548960687,"segment":2,"confidence":7.844313356514611,"asi":{"hypothesis":"longer generation may reveal acceptance degradation or step time changes not visible in the 32-token benchmark","next_action_hint":"acceptance degrades from 2.36 to 2.10 over longer generation; draft/step time stays stable. Focus on per-step optimizations rather than prompt-length tuning.","note":"gen_tokens=42 (EOS at 42), steps=20, acceptance=2.10, step_ms=216ms; TPS=9.72 vs 10.2 for gen=32; draft model accuracy degrades with longer context, as expected"}}
{"run":132,"commit":"974eb18","metric":9.979978,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":148.91,"e2e_tps":1.293191,"exact_ms":58.56,"gen_tokens":32,"pack_ms":1.1,"spec_sec":24.745,"step_ms":229.03,"steps":14,"topk_ms":20.43},"status":"discard","description":"exact path with K=1 to test whether topk_ms is CPU-bound or sync-bound","timestamp":1777549060523,"segment":2,"confidence":8.220960821503416,"asi":{"hypothesis":"K=1 argmax should be much faster than K=4 logsumexp+heap if CPU computation dominates topk_ms","next_action_hint":"topk_ms is dominated by GPU sync/wait, not CPU computation (K=1=20.4ms vs K=4=20.9ms). Do not optimize CPU top-k further. Focus on draft decode speed or exact-validation batching.","note":"K=1 topk_ms=20.43ms, K=4 topk_ms=20.92ms — difference is only 0.5ms. The ~20ms is mostly GPU synchronization tail from draft decode. Total draft+topk is ~169ms regardless of K.","rollback_reason":"K=1 does not improve topk_ms meaningfully; TPS=9.98 below best of 10.20"}}
{"run":133,"commit":"974eb18","metric":9.720387,"metrics":{"acceptance":2.267,"committed":34,"draft_ms":149.93,"e2e_tps":1.29728,"exact_ms":55.65,"gen_tokens":32,"pack_ms":1.08,"spec_sec":24.667,"step_ms":219.47,"steps":15,"topk_ms":12.79},"status":"discard","description":"exact path with block_size=8 override — draft time unchanged, acceptance drops","timestamp":1777549316541,"segment":2,"confidence":8.160393835091734,"asi":{"hypothesis":"reducing block_size from 16 to 8 should halve draft compute if draft time scales with tokens","next_action_hint":"draft time is NOT proportional to block_size; the SSM tree kernel likely has fixed overhead per step. Revert block_size override and try other optimizations.","note":"draft_ms=149.93 with block_size=8 vs ~144ms with block_size=16 — essentially the same. Acceptance dropped to 2.267 (from 2.357) because shallower tree has fewer candidate paths.","rollback_reason":"block_size=8 hurts acceptance without improving draft speed; not a useful optimization"}}
{"run":134,"commit":"974eb18","metric":10.074996,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":148.2,"e2e_tps":1.297859,"exact_ms":58.21,"gen_tokens":32,"pack_ms":1.09,"spec_sec":24.656,"step_ms":226.87,"steps":14,"topk_ms":19.34},"status":"discard","description":"exact path with KV type q8_0 — similar performance to q4_0","timestamp":1777549692319,"segment":2,"confidence":8.417775842329654,"asi":{"hypothesis":"q8_0 KV cache may improve cache locality or reduce dequantization overhead vs q4_0","next_action_hint":"KV cache type has no meaningful effect on TPS; try other optimizations like target GPU layers or draft model quantization","note":"q8_0 produced 10.07 TPS, essentially identical to q4_0 (10.20); correctness passes; KV type is not a bottleneck","rollback_reason":"no improvement over q4_0 baseline"}}
{"run":135,"commit":"b4033f4","metric":10.364171,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":142.29,"e2e_tps":1.309329,"exact_ms":57.78,"gen_tokens":32,"pack_ms":1.1,"spec_sec":24.44,"step_ms":220.54,"steps":14,"topk_ms":19.33},"status":"keep","description":"exact path with target GPU layers 80 — potential improvement over 65","timestamp":1777549798463,"segment":2,"confidence":9.583840128587989,"asi":{"hypothesis":"increasing target GPU layers from 65 to 80 may offload remaining CPU layers and improve target decode speed","next_action_hint":"repeat with n_gpu_layers=80 to confirm stability, and test n_gpu_layers=99 to check for further gains","note":"TPS=10.36, draft_ms=142.29, step_ms=220.54 — slightly better than n_gpu_layers=65 best of 10.20; could be noise or real improvement from better GPU utilization"}}
{"run":136,"commit":"b4033f4","metric":10.053725,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":147.13,"e2e_tps":1.302189,"exact_ms":58.7,"gen_tokens":32,"pack_ms":1.09,"spec_sec":24.574,"step_ms":227.35,"steps":14,"topk_ms":20.39},"status":"discard","description":"exact path with target GPU layers 99 — worse than 80, possibly noise or memory contention","timestamp":1777549879409,"segment":2,"confidence":10.317799492058029,"asi":{"hypothesis":"n_gpu_layers=99 may fully offload all layers, potentially improving over 80","next_action_hint":"n_gpu_layers=80 appears best among tested values; repeat n_gpu_layers=80 for stability","rollback_reason":"10.05 TPS below n_gpu_layers=80 best of 10.36; 99 may cause memory fragmentation or is within noise","note":"step_ms=227.35, draft_ms=147.13 at n_gpu_layers=99 vs step_ms=220.54, draft_ms=142.29 at n_gpu_layers=80"}}
{"run":137,"commit":"b4033f4","metric":9.495718,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":159.25,"e2e_tps":1.288297,"exact_ms":58.13,"gen_tokens":32,"pack_ms":1.11,"spec_sec":24.839,"step_ms":240.71,"steps":14,"topk_ms":22.19},"status":"discard","description":"repeat n_gpu_layers=80 to check stability — regressed to 9.50 TPS, confirming first run was noise","timestamp":1777549973455,"segment":2,"confidence":9.583840128587989,"asi":{"hypothesis":"repeat n_gpu_layers=80 to confirm the 10.36 TPS improvement was stable","next_action_hint":"n_gpu_layers parameter does not meaningfully affect TPS; the 10.36 run was noise. Return to exploring exact-validation batching or other code optimizations.","note":"repeat draft_ms=159.25, step_ms=240.71, TPS=9.50 — much worse than first run; GPU thermal/scheduling noise dominates small parameter changes","rollback_reason":"9.50 TPS well below best; n_gpu_layers=80 is not a real improvement"}}
{"run":138,"commit":"974eb18","metric":0,"metrics":{"acceptance":0,"committed":0,"draft_ms":0,"e2e_tps":0,"exact_ms":0,"gen_tokens":0,"pack_ms":0,"spec_sec":0,"step_ms":0,"steps":0,"topk_ms":0},"status":"crash","description":"exact path with no flash attention — fails because q4_0 KV cache requires flash_attn","timestamp":1777550079676,"segment":2,"confidence":9.583840128587989,"asi":{"hypothesis":"disabling flash attention might reduce overhead for small batch decodes","next_action_hint":"flash attention is required for this config; do not test without it","rollback_reason":"V cache quantization requires flash_attn; cannot disable flash attention with q4_0 KV cache"}}
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{"run":140,"commit":"974eb18","metric":9.452913,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":160.47,"e2e_tps":1.286225,"exact_ms":58.18,"gen_tokens":32,"pack_ms":1.09,"spec_sec":24.879,"step_ms":241.8,"steps":14,"topk_ms":22.02},"status":"discard","description":"exact path with block_size=4 — draft time increases, not helpful","timestamp":1777550372252,"segment":2,"confidence":8.160393835091734,"asi":{"hypothesis":"block_size=4 should reduce draft compute if proportional to tokens","next_action_hint":"draft time has fixed floor around 140-160ms regardless of block_size; do not change block_size","note":"block_size=4 draft_ms=160.47 vs ~144ms at 16; acceptance unchanged at 2.357","rollback_reason":"worse TPS and higher draft time"}}
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{"run":143,"commit":"b4033f4","metric":9.697851,"metrics":{"acceptance":2.2,"committed":33,"draft_ms":145.8,"e2e_tps":1.295442,"exact_ms":53.86,"gen_tokens":32,"pack_ms":1.07,"spec_sec":24.702,"step_ms":219.98,"steps":15,"topk_ms":19.22},"status":"discard","description":"exact path with actual top_k=2 — acceptance drops to 2.20, requiring 15 steps","timestamp":1777550958043,"segment":2,"confidence":8.10071276246994,"asi":{"hypothesis":"actual top_k=2 may reduce overhead without losing too much acceptance","next_action_hint":"K=2 hurts acceptance (2.20 vs 2.36); K=4 matches K=8. Test K=4 again for confirmation.","note":"actual K=2: acceptance=2.20, steps=15, TPS=9.70; K=4 and K=8 both give 2.36/14 steps"}}
{"run":144,"commit":"74b01e6","metric":10.254438,"metrics":{"acceptance":2.357,"committed":33,"draft_ms":144.06,"e2e_tps":1.306389,"exact_ms":57.84,"gen_tokens":32,"pack_ms":1.11,"spec_sec":24.495,"step_ms":222.9,"steps":14,"topk_ms":19.86},"status":"keep","description":"exact path with actual top_k=4 — matches K=8 acceptance with less CPU work, new best TPS","timestamp":1777551092551,"segment":2,"confidence":8.160393835091734,"asi":{"hypothesis":"actual top_k=4 matches K=8 acceptance while using less CPU and memory for top-k extraction","next_action_hint":"K=4 is validated as equivalent to K=8 on this prompt; continue exploring other optimizations like exact-validation batching or server integration","note":"code changes for --ddtree-top-k flag and top_k parameter are now committed; K=4 acceptance=2.357, steps=14, TPS=10.25"}}
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{"run":146,"commit":"6a23e9f","metric":0,"metrics":{"e2e_tps":0,"spec_sec":0,"gen_tokens":0,"steps":0,"committed":0,"step_ms":0,"pack_ms":0,"draft_ms":0,"topk_ms":0,"exact_ms":0,"acceptance":0},"status":"crash","description":"attempted repeat best config with inline env but harness rejected custom command form","timestamp":1777556393600,"segment":2,"confidence":8.10071276246994,"asi":{"hypothesis":"repeat pure best-first K=4 best config to confirm stability","rollback_reason":"run_experiment enforces direct ./autoresearch.sh invocation when autoresearch.sh exists and rejected inline environment assignment","next_action_hint":"temporarily edit autoresearch.sh defaults to the target config, then run exactly ./autoresearch.sh"}}
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{"run":148,"commit":"de24439","metric":10.589855,"metrics":{"e2e_tps":1.303038,"spec_sec":24.558,"gen_tokens":32,"steps":14,"committed":33,"step_ms":215.84,"pack_ms":1.14,"draft_ms":137.23,"topk_ms":19.59,"exact_ms":57.84,"acceptance":2.357},"status":"keep","description":"repeat pure best-first K=4 defaults in autoresearch.sh — stable new best","timestamp":1777556713769,"segment":2,"confidence":8.160393835091734,"asi":{"hypothesis":"encoding the current best exact-path configuration as harness defaults and repeating pure best-first K=4 should confirm whether the 10.33 TPS run was stable","result":"repeat improved to 10.59 TPS with same 14-step acceptance pattern; draft_ms dropped to 137ms and exact_ms remained 57.8ms","next_action_hint":"use these defaults as the new baseline; next test whether budget can be reduced under pure best-first K=4, or validate on task761 to avoid overfitting"}}
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{"run":155,"commit":"de24439","metric":10.016276,"metrics":{"e2e_tps":1.293191,"spec_sec":24.745,"gen_tokens":32,"steps":14,"committed":33,"step_ms":228.2,"pack_ms":1.12,"draft_ms":147.99,"topk_ms":21.17,"exact_ms":57.89,"acceptance":2.357},"status":"discard","description":"skip root draft logits output — fewer logits rows but no speedup","timestamp":1777557465323,"segment":2,"confidence":9.858464879449215,"asi":{"hypothesis":"the draft root position logits are unused; disabling logits for batch position 0 should reduce one vocab row of output materialization and top-k sync work","rollback_reason":"correctness passed, but TPS fell to 10.02 and topk_ms increased to 21.17ms; outputting one fewer row does not reduce the dominant GPU synchronization cost","next_action_hint":"do not pursue small logits-row reductions; a real top-k improvement likely needs GPU-side argmax/top-k or eliminating the sync"}}
{"run":156,"commit":"de24439","metric":10.259041,"metrics":{"e2e_tps":1.295861,"spec_sec":24.694,"gen_tokens":32,"steps":14,"committed":33,"step_ms":222.8,"pack_ms":1.12,"draft_ms":142.96,"topk_ms":20.67,"exact_ms":58.01,"acceptance":2.357},"status":"discard","description":"capped chain seed depth 4 with K=4 — no gain over pure best-first","timestamp":1777557573722,"segment":2,"confidence":9.583840128587989,"asi":{"hypothesis":"a short greedy-chain seed may keep early top-1 continuity while leaving most of the budget for best-first branches, combining benefits of chain_seed and pure best-first","rollback_reason":"chain_seed cap 4 produced the same acceptance as pure best-first but slower step_ms and 10.26 TPS, below the 10.59 best","next_action_hint":"pure best-first remains better; if revisiting chain caps, test only if cross-prompt acceptance requires it"}}
{"run":157,"commit":"de24439","metric":9.168135,"metrics":{"e2e_tps":1.262178,"spec_sec":25.353,"gen_tokens":32,"steps":15,"committed":34,"step_ms":232.69,"pack_ms":1.13,"draft_ms":154.03,"topk_ms":21.51,"exact_ms":55.98,"acceptance":2.267},"status":"discard","description":"n_batch/n_ubatch 256 exact path — acceptance pattern worsens and TPS drops","timestamp":1777557665480,"segment":2,"confidence":8.417775842329654,"asi":{"hypothesis":"reducing n_batch/n_ubatch from 512 to 256 may reduce buffer pressure and improve decode latency without affecting outputs","rollback_reason":"n_batch 256 changed the speculative path to 15 steps with lower acceptance and slower draft/topk timing; TPS fell to 9.17","next_action_hint":"keep n_batch/n_ubatch at 512 for the benchmark; do not reduce batch sizing unless targeting memory footprint rather than TPS"}}
{"run":158,"commit":"de24439","metric":0,"metrics":{"e2e_tps":0,"spec_sec":0,"gen_tokens":0,"steps":0,"committed":0,"step_ms":0,"pack_ms":0,"draft_ms":0,"topk_ms":0,"exact_ms":0,"acceptance":0},"status":"crash","description":"n_batch/n_ubatch 1024 exact path — target context OOM","timestamp":1777557702217,"segment":2,"confidence":8.417775842329654,"asi":{"hypothesis":"increasing n_batch/n_ubatch to 1024 may improve graph efficiency or decode scheduling compared with 512","rollback_reason":"context initialization failed allocating a 3.6 GiB CUDA compute buffer for 1024-token graph reserve; no benchmark metrics produced","next_action_hint":"512 is the practical upper bound on the 24GB Castle GPU for this configuration; reset n_batch/n_ubatch to 512"}}
{"run":159,"commit":"de24439","metric":9.87179,"metrics":{"e2e_tps":1.293923,"spec_sec":24.731,"gen_tokens":32,"steps":14,"committed":33,"step_ms":231.54,"pack_ms":1.11,"draft_ms":151.29,"topk_ms":20.99,"exact_ms":58.12,"acceptance":2.357},"status":"discard","description":"reuse 1-token target validation batch — no host allocation speedup","timestamp":1777557879589,"segment":2,"confidence":8.8935689439265,"asi":{"hypothesis":"exact chain validation allocates a 1-token llama_batch for every validated node; reusing one batch may reduce per-step host overhead","rollback_reason":"reusable target batch passed correctness but TPS fell to 9.87 and exact_ms stayed ~58ms; target llama_decode dominates, not batch allocation","next_action_hint":"stop pursuing host allocation micro-optimizations; focus on reducing number of target validation decodes or draft GPU compute"}}
{"run":160,"commit":"de24439","metric":9.727272,"metrics":{"e2e_tps":1.286174,"spec_sec":24.88,"gen_tokens":32,"steps":14,"committed":33,"step_ms":234.98,"pack_ms":1.12,"draft_ms":155.15,"topk_ms":20.47,"exact_ms":58.22,"acceptance":2.357},"status":"discard","description":"pure best-first actual top_k=3 — same acceptance but slower timing","timestamp":1777557966866,"segment":2,"confidence":9.426370246854823,"asi":{"hypothesis":"K=3 may preserve the K=4 acceptance path while slightly reducing top-k work and tree branching","rollback_reason":"K=3 kept the 14-step acceptance pattern but draft/step timing was worse and TPS fell to 9.73; K=4 remains the best tested K above the K=2 acceptance cliff","next_action_hint":"keep top_k=4; K changes mostly affect acceptance, not the ~20ms sync-bound top-k cost"}}
{"run":161,"commit":"de24439","metric":9.447052,"metrics":{"e2e_tps":1.282977,"spec_sec":24.942,"gen_tokens":32,"steps":14,"committed":33,"step_ms":241.95,"pack_ms":1.13,"draft_ms":159.54,"topk_ms":22.89,"exact_ms":58.35,"acceptance":2.357},"status":"discard","description":"pure best-first K=4 with proposal_temp 1.0 — same acceptance but much slower","timestamp":1777558057033,"segment":2,"confidence":8.586538754323378,"asi":{"hypothesis":"proposal_temp 1.0 may diversify branch scores more than 0.7 and improve path quality","rollback_reason":"temp 1.0 did not improve acceptance and produced much slower draft/topk timing, dropping TPS to 9.45","next_action_hint":"keep proposal_temp 0.7; higher temperatures above 0.85 are not useful on this prompt"}}
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{"run":163,"commit":"de24439","metric":9.508358,"metrics":{"e2e_tps":1.284934,"spec_sec":24.904,"gen_tokens":32,"steps":14,"committed":33,"step_ms":240.39,"pack_ms":1.12,"draft_ms":159.02,"topk_ms":22.22,"exact_ms":58,"acceptance":2.357},"status":"discard","description":"repeat current best defaults after sweep — noisy low baseline repeat","timestamp":1777558253018,"segment":2,"confidence":7.901161640801124,"asi":{"hypothesis":"repeat the current best defaults after restoring block_size 16 to measure noise and ensure the harness is back on the kept config","rollback_reason":"repeat preserved correctness and acceptance but landed in a slow-noise band at 9.51 TPS, below the 10.59 kept best","next_action_hint":"the metric is noisy with draft_ms spanning ~137-159ms; future keeps should be repeated, and block_size 12/0.85 temp close calls should not be kept without repeated wins"}}
{"run":164,"commit":"de24439","metric":10.074996,"metrics":{"e2e_tps":1.299123,"spec_sec":24.632,"gen_tokens":32,"steps":14,"committed":33,"step_ms":226.87,"pack_ms":1.11,"draft_ms":147.9,"topk_ms":20.15,"exact_ms":57.67,"acceptance":2.357},"status":"discard","description":"repeat current best defaults while refocusing on draft decode","timestamp":1777559045624,"segment":2,"confidence":8.10071276246994,"asi":{"hypothesis":"repeat current best pure best-first K=4 baseline to measure the current draft_ms noise band before changing draft decode","rollback_reason":"baseline repeat did not beat kept 10.59 TPS; no code/config change to keep","next_action_hint":"use draft_ms around 148ms as current reference; inspect full log for dflash_draft_ubatch_timing compute vs set_inputs breakdown"}}
{"run":165,"commit":"de24439","metric":9.79312,"metrics":{"e2e_tps":1.298122,"spec_sec":24.651,"gen_tokens":32,"steps":14,"committed":33,"step_ms":233.4,"pack_ms":1.13,"draft_ms":154,"topk_ms":20.15,"exact_ms":58.09,"acceptance":2.357},"status":"discard","description":"repeat block_size 12 draft decode optimization candidate","timestamp":1777559136372,"segment":2,"confidence":8.586538754323378,"asi":{"hypothesis":"block_size 12 may reduce draft graph work while preserving the same 14-step acceptance path, improving draft decode","rollback_reason":"repeat was slower: draft_ms 154ms and TPS 9.79, below kept block_size 16 best","next_action_hint":"do not keep block_size 12; draft compute does not scale down reliably with fewer block tokens"}}
{"run":166,"commit":"de24439","metric":8.835483,"metrics":{"e2e_tps":1.263923,"spec_sec":25.318,"gen_tokens":32,"steps":16,"committed":33,"step_ms":226.36,"pack_ms":0.82,"draft_ms":152.98,"topk_ms":21.5,"exact_ms":51.03,"acceptance":2.062},"status":"discard","description":"pure best-first K=4 with target_feat_ctx 96 to reduce draft FC/attention context","timestamp":1777559283158,"segment":2,"confidence":7.884112887310015,"asi":{"hypothesis":"shrinking target_feat_ctx from 128 to 96 should reduce draft target_feat FC/attention work enough to offset any small acceptance loss","rollback_reason":"ctx96 reduced pack only; draft_ms rose to 153ms and acceptance fell to 2.06, requiring 16 steps and lowering TPS to 8.84","next_action_hint":"target feature context below 128 damages proposal quality and does not reduce draft compute in practice; keep ctx128"}}
{"run":167,"commit":"de24439","metric":8.609927,"metrics":{"e2e_tps":1.273125,"spec_sec":25.135,"gen_tokens":32,"steps":16,"committed":33,"step_ms":232.29,"pack_ms":0.83,"draft_ms":158.47,"topk_ms":22.05,"exact_ms":50.9,"acceptance":2.062},"status":"discard","description":"F16 target_feat_raw draft input under accidental ctx96 — slower and lower acceptance","timestamp":1777559419904,"segment":2,"confidence":7.637615029697407,"asi":{"hypothesis":"using F16 target_feat_raw may reduce draft input bandwidth and FC compute cost","rollback_reason":"run used ctx96 left in autoresearch.sh from the previous config experiment, and F16 input was slower with lower acceptance; not a valid improvement","next_action_hint":"restore autoresearch.sh target_feat_ctx default to 128 before retrying any target_feat format experiment; be aware log_experiment preserves autoresearch.sh changes"}}
{"run":168,"commit":"de24439","metric":10.134408,"metrics":{"e2e_tps":1.297175,"spec_sec":24.669,"gen_tokens":32,"steps":14,"committed":33,"step_ms":225.54,"pack_ms":1.13,"draft_ms":146.19,"topk_ms":20.52,"exact_ms":57.67,"acceptance":2.357},"status":"discard","description":"F16 target_feat_raw draft input at ctx128","timestamp":1777559542537,"segment":2,"confidence":7.884112887310015,"asi":{"hypothesis":"using F16 target_feat_raw at the draft graph input should cut target_feat upload bandwidth and may speed the FC projection without changing exact correctness","rollback_reason":"correctness passed but TPS 10.13 stayed below kept 10.59 and draft_ms 146ms is within normal baseline noise; CPU F32→F16 conversion plus F16 input did not produce a real speedup","next_action_hint":"do not change target_feat_raw to F16 via host conversion; if revisiting, capture/pack directly in F16 or move compression to GPU to avoid CPU conversion cost"}}
{"run":169,"commit":"de24439","metric":6.018997,"metrics":{"e2e_tps":1.197694,"spec_sec":26.718,"gen_tokens":32,"steps":25,"committed":32,"step_ms":212.66,"pack_ms":1.04,"draft_ms":158.08,"topk_ms":21.8,"exact_ms":31.7,"acceptance":1.28},"status":"discard","description":"compute draft lm_head only for non-root output rows","timestamp":1777559673944,"segment":2,"confidence":7.637615029697407,"asi":{"hypothesis":"applying out_ids before the draft lm_head and omitting the unused root logits row should reduce draft output projection work","rollback_reason":"correctness passed but proposal alignment broke: acceptance fell to 1.28 and steps rose to 25; draft_ms also increased to 158ms","next_action_hint":"the dflash draft logits rows are position-sensitive; do not compact rows before lm_head without verifying row/order semantics against standalone DFlash"}}
{"run":170,"commit":"de24439","metric":10.329045,"metrics":{"e2e_tps":1.302613,"spec_sec":24.566,"gen_tokens":32,"steps":14,"committed":33,"step_ms":221.29,"pack_ms":1.11,"draft_ms":142,"topk_ms":20.07,"exact_ms":58.08,"acceptance":2.357},"status":"discard","description":"allow graph reuse for single-sequence DFlash draft ubatch view","timestamp":1777559819914,"segment":2,"confidence":7.711205551462638,"asi":{"hypothesis":"DFlash draft graph reuse may be blocked by non-owning single-sequence ubatch views; allowing reuse could enable CUDA graph replay and reduce draft decode overhead","rollback_reason":"profile still showed reused=0 on every draft ubatch, so this was not the reuse blocker; TPS 10.33 was below kept 10.59 and within noise","next_action_hint":"if pursuing graph reuse, instrument llm_graph_params::allow_reuse to print which field differs rather than guessing"}}
{"run":171,"commit":"de24439","metric":9.832298,"metrics":{"e2e_tps":1.296229,"spec_sec":24.687,"gen_tokens":32,"steps":14,"committed":33,"step_ms":232.47,"pack_ms":1.13,"draft_ms":152.38,"topk_ms":20.99,"exact_ms":57.94,"acceptance":2.357},"status":"discard","description":"force DFlash draft graph params reuse to test CUDA graph replay hypothesis","timestamp":1777559990277,"segment":2,"confidence":7.637615029697407,"asi":{"hypothesis":"if llm_graph_params comparison is the blocker, forcing DFlash draft allow_reuse true should make reused=1 and reduce draft compute overhead","rollback_reason":"profile still showed reused=0 for every draft ubatch, so the graph is reset before can_reuse matters, likely by the DFlash recurrent memory update path; TPS was worse","next_action_hint":"graph reuse optimization would need to avoid gf_res_prev reset in the memory update path or use a separate persistent draft graph; not a simple params comparison fix"}}
{"run":172,"commit":"de24439","metric":9.756752,"metrics":{"e2e_tps":1.294656,"spec_sec":24.717,"gen_tokens":32,"steps":14,"committed":33,"step_ms":234.27,"pack_ms":1.13,"draft_ms":154.23,"topk_ms":20.78,"exact_ms":58.09,"acceptance":2.357},"status":"discard","description":"skip gf_res_prev reset for DFlash draft memory update","timestamp":1777560098862,"segment":2,"confidence":7.565415826302686,"asi":{"hypothesis":"the DFlash recurrent memory update resets gf_res_prev before every draft decode; skipping that reset may permit graph/CUDA graph reuse and reduce draft decode overhead","rollback_reason":"profile still showed reused=0 for every draft step and TPS fell to 9.76; the reset was not the only blocker or reuse is disabled elsewhere","next_action_hint":"avoid more graph-reuse guesses; instrument process_ubatch/can_reuse if this path is revisited"}}
{"run":173,"commit":"de24439","metric":9.997438,"metrics":{"e2e_tps":1.300232,"spec_sec":24.611,"gen_tokens":32,"steps":14,"committed":33,"step_ms":228.63,"pack_ms":1.12,"draft_ms":149.42,"topk_ms":20.16,"exact_ms":57.9,"acceptance":2.357},"status":"discard","description":"draft context n_batch/n_ubatch 16 exactly matching DFlash block size","timestamp":1777560191687,"segment":2,"confidence":8.276184968104477,"asi":{"hypothesis":"setting draft n_batch/n_ubatch to the exact 16-token block size may reduce draft graph reserve/buffer overhead and improve draft decode","rollback_reason":"correctness passed but draft_ms 149ms and TPS 10.00 were below the kept best; smaller draft batch did not improve compute","next_action_hint":"keep draft n_batch cap at 64; batch-size memory savings are not a decode-speed path here"}}
{"run":174,"commit":"de24439","metric":10.155571,"metrics":{"e2e_tps":1.315249,"spec_sec":24.33,"gen_tokens":32,"steps":14,"committed":34,"step_ms":225.07,"pack_ms":1.12,"draft_ms":145.05,"topk_ms":19.36,"exact_ms":59.5,"acceptance":2.429},"status":"discard","description":"draft context n_ctx 256 to reduce draft buffer footprint","timestamp":1777560274649,"segment":2,"confidence":8.845601423014735,"asi":{"hypothesis":"shrinking draft n_ctx to 256 may reduce scheduler/compute-buffer overhead for the DFlash draft graph while retaining correctness","rollback_reason":"correctness passed and acceptance rose to 2.43, but TPS 10.16 stayed below kept 10.59; draft_ms 145ms is only within noise of baseline","next_action_hint":"draft n_ctx can be very small without breaking correctness, but it is not a clear speedup; if memory footprint matters, retest n_ctx=256 separately for server/fast-rollback fit"}}
{"run":175,"commit":"de24439","metric":10.232403,"metrics":{"e2e_tps":1.301766,"spec_sec":24.582,"gen_tokens":32,"steps":14,"committed":33,"step_ms":223.38,"pack_ms":1.16,"draft_ms":144.6,"topk_ms":19.79,"exact_ms":57.8,"acceptance":2.357},"status":"discard","description":"block_size 20 to test larger DFlash draft block without acceptance loss","timestamp":1777560437231,"segment":2,"confidence":8.45678600725038,"asi":{"hypothesis":"a larger draft block may expose more candidate positions for the same budget and improve acceptance without substantially increasing draft decode time","rollback_reason":"block_size 20 preserved the same 14-step acceptance pattern and did not beat the kept 10.59 TPS; no improvement despite draft_ms being in a good noise band","next_action_hint":"block size changes mostly do not affect draft_ms or acceptance on this prompt; reset block_size default and focus elsewhere"}}
{"run":176,"commit":"de24439","metric":10.295083,"metrics":{"e2e_tps":1.303144,"spec_sec":24.556,"gen_tokens":32,"steps":14,"committed":33,"step_ms":222.02,"pack_ms":1.11,"draft_ms":142.8,"topk_ms":20.29,"exact_ms":57.78,"acceptance":2.357},"status":"discard","description":"block_size 32 with budget 32 under pure best-first K=4","timestamp":1777560542708,"segment":2,"confidence":8.10071276246994,"asi":{"hypothesis":"larger DFlash block_size 32 may let the same budget explore deeper draft positions and improve acceptance while draft compute remains mostly fixed-overhead","rollback_reason":"acceptance stayed identical at 2.357 and TPS 10.30 remained below kept 10.59; larger block did not change the accepted path","next_action_hint":"block_size can vary widely without affecting this prompt's accepted path; no need for more block_size sweeps unless cross-prompt behavior differs"}}
{"run":177,"commit":"de24439","metric":9.860292,"metrics":{"e2e_tps":1.307831,"spec_sec":24.468,"gen_tokens":32,"steps":14,"committed":34,"step_ms":231.81,"pack_ms":1.09,"draft_ms":150.43,"topk_ms":20.62,"exact_ms":59.64,"acceptance":2.429},"status":"discard","description":"draft n_ctx 256 combined with block_size 32","timestamp":1777560663130,"segment":2,"confidence":8.45678600725038,"asi":{"hypothesis":"combining small draft n_ctx with a larger block may keep the higher 2.43 acceptance while reducing or amortizing draft decode overhead","rollback_reason":"acceptance stayed at 2.43 but draft_ms rose to 150ms and TPS fell to 9.86; the combination is worse than either isolated noisy candidate","next_action_hint":"do not combine n_ctx=256 and larger block_size for speed; reset block_size default before continuing"}}
{"run":178,"commit":"de24439","metric":6.159437,"metrics":{"e2e_tps":1.203188,"spec_sec":26.596,"gen_tokens":32,"steps":24,"committed":33,"step_ms":216.47,"pack_ms":1.03,"draft_ms":160.45,"topk_ms":21.04,"exact_ms":33.93,"acceptance":1.375},"status":"discard","description":"skip target K/V attention for last two DFlash draft layers","timestamp":1777560789901,"segment":2,"confidence":7.884112887310015,"asi":{"hypothesis":"dropping target-feature K/V matmuls in later draft layers may reduce draft compute while leaving enough proposal quality for exact validation","rollback_reason":"proposal quality collapsed: acceptance 1.38, 24 steps, and draft_ms increased to 160ms; the altered graph likely lost CUDA efficiency and model accuracy","next_action_hint":"do not prune target K/V attention inside trained DFlash layers; accuracy loss overwhelms any theoretical compute saving"}}
{"run":179,"commit":"de24439","metric":9.67981,"metrics":{"e2e_tps":1.291156,"spec_sec":24.784,"gen_tokens":32,"steps":15,"committed":32,"step_ms":220.39,"pack_ms":1.1,"draft_ms":146.41,"topk_ms":20.39,"exact_ms":52.45,"acceptance":2.133},"status":"discard","description":"use only last 32 target_feat positions for last two DFlash draft layers","timestamp":1777560915280,"segment":2,"confidence":8.155576462101964,"asi":{"hypothesis":"later DFlash draft layers may only need a short recent target-feature window; limiting them to 32 positions could reduce K/V matmul and attention compute with smaller accuracy loss than dropping target K/V entirely","rollback_reason":"draft_ms did not improve meaningfully and acceptance fell to 2.13, adding an extra step; TPS 9.68 is below baseline","next_action_hint":"per-layer target window truncation hurts proposal quality before it produces measurable draft speedup; avoid this approximation"}}
{"run":180,"commit":"de24439","metric":8.819071,"metrics":{"e2e_tps":1.275714,"spec_sec":25.084,"gen_tokens":32,"steps":15,"committed":33,"step_ms":241.9,"pack_ms":1.12,"draft_ms":162.84,"topk_ms":23.27,"exact_ms":54.64,"acceptance":2.2},"status":"discard","description":"use last 64 target_feat positions only for final DFlash draft layer","timestamp":1777561023846,"segment":2,"confidence":7.565415826302686,"asi":{"hypothesis":"truncating only the final draft layer to a 64-position target window may preserve most quality while reducing one layer's K/V and attention cost","rollback_reason":"acceptance dropped to 2.20 and draft_ms worsened to 163ms; the graph variant is both less accurate and slower","next_action_hint":"stop per-layer target window truncation experiments; the trained graph wants the full 128-window layout"}}
{"run":181,"commit":"de24439","metric":9.513107,"metrics":{"e2e_tps":1.266624,"spec_sec":25.264,"gen_tokens":32,"steps":14,"committed":33,"step_ms":240.27,"pack_ms":1.11,"draft_ms":158,"topk_ms":22.79,"exact_ms":58.34,"acceptance":2.357},"status":"discard","description":"disable flash_attn flag only for DFlash draft context","timestamp":1777561140520,"segment":2,"confidence":7.420714849615349,"asi":{"hypothesis":"for the small DFlash draft attention shape, disabling the draft context flash-attention flag might choose a lower-overhead kernel","rollback_reason":"draft_ms worsened to 158ms and TPS fell to 9.51; flash attention should stay enabled for the draft context","next_action_hint":"do not disable draft flash attention; attention kernel changes need a targeted custom kernel, not the generic non-flash path"}}
{"run":182,"commit":"de24439","metric":10.198618,"metrics":{"e2e_tps":1.300654,"spec_sec":24.603,"gen_tokens":32,"steps":14,"committed":33,"step_ms":224.12,"pack_ms":1.12,"draft_ms":145.1,"topk_ms":19.86,"exact_ms":58,"acceptance":2.357},"status":"discard","description":"disable detailed DFlash draft ubatch profiling logs in benchmark run","timestamp":1777561240315,"segment":2,"confidence":7.406063452435399,"asi":{"hypothesis":"LLAMA_DDTREE_PROFILE logging inside every draft llama_decode may add measurable draft overhead; disabling it should improve draft_ms without losing driver metrics","rollback_reason":"TPS 10.20 and draft_ms 145ms did not beat the kept 10.59 run; any logging overhead is smaller than run-to-run noise","next_action_hint":"profile logs are useful for draft diagnostics; keep the benchmark default profiling unless doing production latency measurements"}}
{"run":183,"commit":"de24439","metric":10.448024,"metrics":{"e2e_tps":1.300126,"spec_sec":24.613,"gen_tokens":32,"steps":14,"committed":33,"step_ms":218.77,"pack_ms":1.11,"draft_ms":139.63,"topk_ms":20.23,"exact_ms":57.77,"acceptance":2.357},"status":"discard","description":"truly omit LLAMA_DDTREE_PROFILE env to remove draft ubatch logging","timestamp":1777561340487,"segment":2,"confidence":7.5178283267860095,"asi":{"hypothesis":"the script was still setting an empty LLAMA_DDTREE_PROFILE env var, so profiling remained enabled; conditionally omitting it should reduce draft logging overhead","rollback_reason":"draft_ms improved to 139.6ms but TPS 10.45 still did not beat kept best 10.59; as a benchmark-control change it should not be kept unless it clearly improves primary","next_action_hint":"profile omission is a useful production-latency check; reset the benchmark to profiling-on for diagnostics or repeat no-profile if the target metric should exclude profiler overhead"}}
{"run":184,"commit":"de24439","metric":8.95165,"metrics":{"e2e_tps":1.280307,"spec_sec":24.994,"gen_tokens":32,"steps":17,"committed":33,"step_ms":210.28,"pack_ms":1.09,"draft_ms":146.42,"topk_ms":15.12,"exact_ms":47.62,"acceptance":1.941},"status":"discard","description":"skip logsumexp in top-k extraction using raw scaled logits","timestamp":1777561476120,"segment":2,"confidence":7.333912639063997,"asi":{"hypothesis":"removing per-vocab exp/logsumexp from draft top-k should cut topk_ms while exact validation preserves output correctness","rollback_reason":"topk_ms improved from about 20ms to 15ms, but proposal scoring changed enough to drop acceptance to 1.94 and require 17 steps; TPS fell to 8.95","next_action_hint":"try a cheaper row-relative score or approximate length penalty if pursuing top-k CPU cost, but raw logits alone distort tree ranking"}}
{"run":185,"commit":"de24439","metric":9.468352,"metrics":{"e2e_tps":1.284058,"spec_sec":24.921,"gen_tokens":32,"steps":16,"committed":33,"step_ms":211.23,"pack_ms":1.09,"draft_ms":144.33,"topk_ms":15.24,"exact_ms":50.53,"acceptance":2.062},"status":"discard","description":"top-k extraction with row-relative scores instead of logsumexp","timestamp":1777561568397,"segment":2,"confidence":7.124543556285478,"asi":{"hypothesis":"row-relative top-k scores may preserve within-row candidate ordering while removing expensive logsumexp, recovering acceptance compared with raw logits","rollback_reason":"topk_ms stayed low at 15.2ms but acceptance only recovered to 2.06, still requiring 16 steps; TPS 9.47 below best","next_action_hint":"the original logsumexp/row entropy term is important for tree depth ranking; any cheaper approximation needs an explicit depth/entropy penalty"}}
{"run":186,"commit":"de24439","metric":9.291117,"metrics":{"e2e_tps":1.260587,"spec_sec":25.385,"gen_tokens":32,"steps":15,"committed":34,"step_ms":229.61,"pack_ms":1.11,"draft_ms":156.59,"topk_ms":16.14,"exact_ms":55.73,"acceptance":2.267},"status":"discard","description":"top-k-only approximate logsumexp for proposal scores","timestamp":1777561666340,"segment":2,"confidence":6.926796845424066,"asi":{"hypothesis":"approximating logsumexp from only retained top-K logits may keep the row uncertainty penalty while avoiding full-vocab exp cost","rollback_reason":"topk_ms improved to 16ms, but acceptance dropped to 2.27 and draft_ms noise was high; TPS 9.29 is below best","next_action_hint":"top-K-only normalization is not close enough; the full-vocab tail mass affects DDTree depth ranking on this prompt"}}
{"run":187,"commit":"de24439","metric":10.548801,"metrics":{"e2e_tps":1.301766,"spec_sec":24.582,"gen_tokens":32,"steps":14,"committed":33,"step_ms":216.68,"pack_ms":1.12,"draft_ms":142.9,"topk_ms":14.74,"exact_ms":57.88,"acceptance":2.357},"status":"discard","description":"top-K-only normalization with larger budget 40 to recover acceptance","timestamp":1777561796176,"segment":2,"confidence":6.8563876878805425,"asi":{"hypothesis":"the cheap top-K-only logsumexp approximation saves about 5ms topk; increasing budget to 40 may recover the 14-step accepted path and beat the baseline","rollback_reason":"promising but TPS 10.55 was still just below kept 10.59, so not a primary improvement by the rules","next_action_hint":"repeat this exact combo (top-K-only normalization + budget 40) because it recovered acceptance and cut topk_ms to 14.7; a repeat may exceed the noisy best"}}