sync : ggml#3912
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* mtmd, arg: fix utf8 handling on windows * also fix ggml_fopen * fix build fail * also fix CLI
Flatten the partition over n_batch * M so every thread participates in
the quantization
| CPU | Model | Test | t/s OLD | t/s NEW | Speedup |
|:--------------------------------|:------------------------------|:-------|----------:|----------:|----------:|
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B IQ4_NL - 4.5 bpw | pp512 | 730.71 | 779.86 | 1.07 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B IQ4_NL - 4.5 bpw | tg128 | 87.88 | 86.79 | 0.99 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B IQ4_XS - 4.25 bpw | pp512 | 725.09 | 1023.31 | 1.41 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B IQ4_XS - 4.25 bpw | tg128 | 83.64 | 83.62 | 1.00 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_0 | pp512 | 820.51 | 924.05 | 1.13 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_0 | tg128 | 90.59 | 92.46 | 1.02 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_1 | pp512 | 776.88 | 872.79 | 1.12 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_1 | tg128 | 89.39 | 90.94 | 1.02 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_K_M | pp512 | 719.28 | 1009.27 | 1.40 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_K_M | tg128 | 80.62 | 80.86 | 1.00 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_K_S | pp512 | 732.29 | 1077.29 | 1.47 |
| Intel(R) Xeon(R) Platinum 8488C | qwen35 0.8B Q4_K_S | tg128 | 86.42 | 83.53 | 0.97 |
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* support bf16 on bin_bcast OP and unary OPs * support the older Intel compiler than 2026.0
…tches (llama/24811) * ggml-webgpu: improve small batches decoding * Add barrier to the NUM_COLS loop in mul-mat-vec
…enabled (llama/24444) The result-checking and test debug paths in ggml-vulkan.cpp call ggml_graph_compute_with_ctx() to compute a CPU reference graph, but that symbol is defined in ggml-cpu, which ggml-vulkan does not link. Enabling -DGGML_VULKAN_CHECK_RESULTS=ON (or -DGGML_VULKAN_RUN_TESTS=ON) therefore fails to link with an unresolved external (e.g. LNK2019 on MSVC, undefined reference on GCC/Clang). This regressed after ggml-cpu was split into its own library. Link ggml-cpu under those two options so the debug builds link again. Signed-off-by: Wyatt Caldwell <218154709+Detensable@users.noreply.github.com>
This trims down some of the shader variant explosion and reduces binary size.
* vulkan: support CONV_3D This is a pretty direct port of conv2d_mm.comp to CONV_3D, done by codex and cleaned up by me. * disable slower perf tests
…LU/NORM (llama/24582) * vulkan: make SQR/SQRT/SIN/COS/CLAMP/LEAKY_RELU use unary.comp * vulkan: make NORM support noncontig * add noncontiguous row test cases for norm/l2_norm, handle this in the CPU backend and l2_norm.comp * fix supports_op for cuda and webgpu
* vulkan-shaders-gen: fail the build when a shader fails to compile vulkan-shaders-gen did not detect shader-compile subprocess failures, so a broken libggml-vulkan could be produced while the build reported success and the breakage only surfaced at run time. execute_command() discarded the child exit code (POSIX waitpid passed nullptr for status; the Windows branch never called GetExitCodeProcess) and string_to_spv decided success only from whether stderr was empty, so a non-zero exit with empty stderr, or a subprocess that failed to launch, was treated as success. Return the child exit code from execute_command() (WEXITSTATUS on POSIX, GetExitCodeProcess on Windows), treat a non-zero exit or non-empty stderr or a launch exception as a failure, and record it in an atomic flag. main() checks the flag after process_shaders() and returns EXIT_FAILURE before writing the output files, so the build stops instead of emitting a broken backend. Fixes #24393 Signed-off-by: liminfei-amd <91481003+liminfei-amd@users.noreply.github.com> * vulkan-shaders-gen: simplify compile_failed access and drop unreachable return Address review feedback on #24450: - Access the std::atomic<bool> compile_failed directly (= / implicit bool) instead of .store()/.load(); the flag stays atomic because the worker threads in process_shaders() set it concurrently. - Remove the unreachable trailing return -1 in execute_command(): on POSIX the child _exit()s after execvp and the parent returns (fork()<0 throws); on Windows the block returns the exit code. Signed-off-by: liminfei-amd <91481003+liminfei-amd@users.noreply.github.com> --------- Signed-off-by: liminfei-amd <91481003+liminfei-amd@users.noreply.github.com>
…ernel-params, cached graphs (llama/24954) * hex-mm: new weight layout and fusion updates * hvx-mm: unroll the new tiled vec_dots to optimize hvx register util * hex-mm: optimize dyn.quant format for q8_0 and q8_1 to reduce overhead in vec_dots. * hvx-mm: parallel quantizer per block for large rows * hvx-mm: simplify and futher optimize dyn.quant and vec_dots * hvx-mm: keep intermediate per tile accumulators in fp16 * hmx-mm: optimize weight dequant by aligning the repacked tiles with the DMA * hmx-mm: remove qweight scratch and just use vtcm_weight * hmx-mm: remove all unused and obsolete code * hmx-mm: the new tiled repack format is here to stay -- rename all x4x2 to _tiled * hmx-mm: improve activation processing with dma prefetch * hex-mm: fix hmx/hvx fallback logic and MUL_MAT_ID allocation (unbreaks OLMoE) * hex-mm: align the weight tiles with dma just like we did in hmx-mm * hex-mm: factor out common mm bits into htp/matmul-ops.h * hex-mm: start moving mm kernel selection to the host * hex-mm: move all of the matmul param compute into the host * hmx-mm: restore pipelined mode * hmx-mm: unroll the dequant functions to optimize register usage * hmx-mm: further improve activation process * hex-mm: use vtcm_seq_alloc for all vtcm allocations and define more common functions * hex-mm: improve mm optimizer to acount for number of activation threads * hex-mm: fix matmul-id kernel params selection (unbreaks OLMoE and LFM) * hexagon: remove support for arch < v73 since HMX is now required for most use-cases * hex-mm: cleanup naming for consistency * hex-mm: make sure matmul fusion accounts for vtcm allocation * hex-mm: minor cleanup for kernel_params definition * hex-mm: replace hardcoded limits with proper checks for vtcm requirements * hex-mm: add support for non-tiled mm as a fallback option and factor out hvx kernels into separate header * hex-mm: remove unused functions * hex-mm: add shorthand for MM_SELECT in run-tool script * hvx-mm: factor out hvx/hmx microkernels and unify matmul entry and dispatch * hex-mm: further cleanup matmul fallback path * hex-mm: refactor matmul entry point and dispatch a bit further * hexagon: update cmake build to enable hmx for everything * hex-ops: optimize kernel_param updates and include summary in the logs * hex-mm: add support for GGML_HEXAGON_MM_SELECT * hex-mm: add hex-common header * hex-mm: pass correct number of tasks to workpool * hex-mm: add proper checks for no-work in dyn.quant tasks * hex-mm: convert all quantizers into a macro * hex-mm: fix hvx-flat fallback to pass all MUL_MAT tests * hex-mm: vectorize q8_1 quantizer * hex-mm: improve fused ffn mm stride handling * hex-mm: consistent use of n_threads and pipeline in kernel_params * hexagon: minor formatting * hex-mm: update MUL_MAT_ID kernel_param handling to make sure host/npu are in sync * hvx-mm: go back to accumulating in fp32 in tiled hvx kernels, more accurate and same perf * hvx-mm: unroll the loops and remove masking that is not needed for tiled accums * hmx-mm: optimize activation processing (slit loops, some unrolling, etc) * hmx-mm: minor optimization for output processing * hex-mm: consistent use of uint32_t and size_t in mm kernels * hex-mm: remove legacy restrictions for rows to be multiple of 256 * hexagon: replace sprintf with snprintf * hex-mm: relax hardcoded nrows checks and rely on VTCM size requirements * hexagon: minor alignment fix * hexagon: fix trailing spaces * hex-mm: relax padding from 256 to 128 (leftovers) * hex-mm: remove redundant checks for weight align to 128 we always use 2D dma for the weights and align them properly * hmx-mm: MUL_MAT_ID better work distribution between hvx threads and hmx tracing * hex-mm: specialize per-token mmid activation handling * hex-profile: update python scripts to handle kernel-params section in the logging output * hex-mm: move n_prefetch (aka dma_depth) into kernel params and remove unused fields * hex-trace: use easier to parse format, simply and fix post-proc scripts * hmx-mm: relax 32 row limit for output processing which helps utilization * hmx-mm: use start-chunk idx for tracing info * hmx-mm: parameterize activation dma pipeline * hexagon: add support for simple graph caching to avoid recomputing kernel-params * hex-mm: remove left-over repack functions * hex-mm: tighten n_prefetch asserts * hex-mm: remove duplicate round/align_up helper * hexagon: cleanup common header used in host/npu * hexagon: update early wakeup threshold * hmx-mm: define cost constants and update solver to assume that repacked ne[1] is padded to 32 * hmx-mm: make precompute_matmul a bit more readable (split into smaller functions, etc) * hex-mm: remove n_threads constraint * hex-mm: minor formatting updates * hex-mm: remove obsolete profiling logs * hex-mm: restore hardcode gate to refuse lm-head to avoid repacking that tensor
* Sycl tp stage1 (llama/1)
* SYCL: tensor parallelism (--split-mode tensor) for dual-GPU
Adds the comm_init/comm_free/comm_allreduce_tensor trio that the
meta-backend queries via get_proc_address to enable backend-specific
all-reduce, mirroring the pattern used by ggml-cuda.cu.
For N=2 (the common dual-GPU case) implements a degenerate ring
all-reduce with two size-branched paths:
* Small (nelem < 32768): FP32 direct memcpy + per-device ADD kernel
chained via depends_on(memcpy_event). 4 SYCL submissions/call.
* Large (nelem >= 32768): BF16-compressed. Each device compresses
FP32 -> BF16 in a local outbox, cross-device memcpys to the peer's
inbox (HALF the PCIe bytes), then decompresses + adds into the
local FP32 partial. 6 SYCL submissions/call but PCIe bytes halved
-- wins for any tensor where PCIe dominates kernel time.
Threshold and BF16 path pattern mirror the CUDA NCCL allreduce.
Storage: ONE persistent uint8_t buffer per device, 4 * nelem bytes
(matches both path layouts: FP32 nelem floats; BF16 outbox+inbox =
2 * nelem uint16_t each). Single alloc+free per device keeps the
SYCL pool's strict-LIFO invariant trivial.
Initial impl handles N=2 FP32 contiguous tensors. Other cases return
false, causing the meta-backend to use its generic butterfly fallback.
Per-call sync is intentionally omitted. SYCL in-order queue semantics
ensure that the meta-backend's next compute on the same per-device
queue waits for our final ADD, and the next allreduce's first op on
the same persistent buffer waits via the same queue. Only comm_free
does an explicit final wait.
OneCCL is NOT used: OneCCL 2021.17 hardcodes single-device-per-process
in communicator_impl.hpp:47 (condition devices.size() == 1), which is
incompatible with llama.cpp's single-process multi-GPU model.
Measured on dual Intel Arc Pro B70 (NEO 26.05.x, oneAPI 2025.3 +
DPC++ nightly):
Llama-3.3-70B Q4_K_M, -sm tensor -fa 1 -ctk f16 -ctv f16:
pp512 = 377.08 t/s (vs 313.65 layer mode = +20.2%)
tg128 = 17.40 t/s (vs 9.74 layer mode = +78.6%)
Qwen3-Coder-Next-80B-A3B Q3_K_M (MoE):
pp512 = 216.56 t/s (vs 156.58 meta-backend butterfly = +38.3%)
tg128 = 17.60 t/s (vs 14.31 meta-backend butterfly = +23.0%)
Qwen3-4B Q4_K_M:
pp64 = 984.51 t/s, tg16 = 49.29 t/s
Llama-3.3-70B in SYCL TP now comfortably beats production layer mode
on both prefill and decode. Coder-Next-80B-A3B (MoE) also wins on
both — the BF16 path is what unlocks the many-medium-allreduces
prefill pattern.
Build/CMake: no changes. No new dependencies. ~210 lines added across
ggml-sycl.h and ggml-sycl.cpp.
* Fix comments
* documentation update to address PR feedback
* Bring over my device-to-device memcpy chagnes
* move the dev2dev_memcpy calls to the upstream 7-parameter variety
* Fix a typo and remove a trailing whitespace
…lama/24706) * ggml : address integer overflows in binary ops CUDA implementation * ggml : add size_t casts to avoid integer overflows * ggml : add more asserts checking integer overflows in binary ops CUDA implementation --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* Add failing test-case to test-backend-ops Extracted from ggml-org/llama.cpp#24072 * Minimize repro with help of AI N = 8 * (65535 - 1) + 1 = 524273 * Port and adjust workaround from LostRuins/koboldcpp@0ba7983 Fall-back should share code, also relax y-z constraint to be inclusive * Add test-case + fallback also for y dim * Fix x-guards which is 2^{31}-1, so inlusive of INT_MAX * Fix overflow problems for transposed copy kernel
* ggml-cpu: fix SVE leftover path in ggml_vec_dot_f32 2D convolutions with kernel size 9 produced different results on SVE enabled ARM devices. After debugging it turned out that ggml_vec_dot_f32 was using data from inactive lanes. Use svmla_f32_m(pg, sum1, ax1, ay1) so inactive lanes retain sum1. * cont : clean-up --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* vulkan: Workaround compiler bug in conv2d coopmat2 path * apply same workaround to CONV_3D * Apply suggestion from @jeffbolznv
danbev
approved these changes
Jun 26, 2026
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