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feat: add ring/ulysses mesh axes and BSHD Ulysses attention for WAN 2.2
Adds dedicated `ring` and `ulysses` mesh axes so hybrid context parallelism does not interfere with weight TP sharding rules. Rewrites _ulysses_attention to keep tensors in BSHD layout through the all-to-all collective, avoiding a full-sequence BHSD transpose before the redistribution — ~34% faster than the original implementation and 8% faster than plain ring at dp=2 cp=8 on v7x-16. - common_types: add RING/ULYSSES axis name constants and axis rules for ulysses_ring hybrid (sequence sharded over [ring, ulysses]) - configs: add ici/dcn ring+ulysses parallelism params and updated mesh_axes, logical_axis_rules, data_sharding, and flash block sizes for all WAN configs - max_utils: extend create_device_mesh to append ring/ulysses axes when present - attention_flax: BSHD-native _ulysses_attention; new _ulysses_ring_attention combining Ulysses all-to-all (ulysses axis) with Tokamax ring (ring axis); routing and cross-attention fallback wired in _apply_attention - pyconfig: prepend ULYSSES_RING_ATTENTION_AXIS_RULES for ulysses_ring modes - bench_remaining.sh, docs: multihost benchmark harness and results Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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‎README.md‎

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Ulysses requires `ici_context_parallelism` greater than 1, and the number of attention heads must be divisible by the context shard count. `flash_block_sizes` tuning is optional and can still be used for hardware-specific tuning.
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For TPU multihost 2D context parallelism, use `attention="ulysses_ring"`.
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This shards self-attention sequence over `context` x `tensor`, runs the Ulysses all-to-all over the `tensor`
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mesh axis, and reuses Tokamax ring attention over the `context` mesh axis. The number of attention heads must
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be divisible by `ici_tensor_parallelism`; a typical multihost setup uses DCN context for the ring axis and ICI
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tensor for the Ulysses axis. On TPU7x, keep `dcn_tensor_parallelism=1` and set `ici_tensor_parallelism >= 2`
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so the dual chiplets exposed as two JAX devices are grouped by Ulysses rather than ring.
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```bash
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python src/maxdiffusion/generate_wan.py \
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src/maxdiffusion/configs/base_wan_i2v_27b.yml \
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attention="ulysses_ring" \
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dcn_context_parallelism=<num_slices> \
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ici_context_parallelism=1 \
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ici_tensor_parallelism=<ulysses_shards_per_slice> \
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...
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```
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In our Wan2.2 I2V benchmarks at 40 inference steps, 81 frames, and `720x1280` resolution, Ulysses improved inference time by roughly `~10%` compared with flash attention, with about `~20s` lower latency on the v6e-8 and v7x-8 TPU setup.
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### Caching Mechanisms

‎bench_remaining.sh‎

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#!/usr/bin/env bash
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set -euo pipefail
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# ── config ────────────────────────────────────────────────────────────────────
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REPO_DIR=/dev/shm/maxdiffusion
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VENV=$REPO_DIR/.venv-tpu
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CONFIG=$REPO_DIR/src/maxdiffusion/configs/base_wan_27b.yml
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RESULTS_ROOT=$REPO_DIR/bench_results
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OUTPUT_ROOT=$REPO_DIR/bench_outputs
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WORKER1_USER=sa_112155357684894056033
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WORKER1_IP=10.154.0.59
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WORKER1_HOST_ALIAS=tpu.2884514015978940116-1-jgVFrB
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SSH_KEY=/home/sagarchapara_google_com/.ssh/google_compute_engine
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SSH_KNOWN_HOSTS=/home/sagarchapara_google_com/.ssh/google_compute_known_hosts
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SSH_OPTS="-T -i $SSH_KEY -o CheckHostIP=no -o HashKnownHosts=no \
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-o HostKeyAlias=$WORKER1_HOST_ALIAS -o IdentitiesOnly=yes \
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-o StrictHostKeyChecking=no -o UserKnownHostsFile=$SSH_KNOWN_HOSTS"
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export LIBTPU_INIT_ARGS=\
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'--xla_tpu_dvfs_p_state=7 '\
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'--xla_tpu_enable_async_collective_fusion_fuse_all_gather=true '\
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'--xla_tpu_megacore_fusion_allow_ags=false '\
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'--xla_enable_async_collective_permute=true '\
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'--xla_tpu_enable_ag_backward_pipelining=true '\
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'--xla_tpu_enable_data_parallel_all_reduce_opt=true '\
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'--xla_tpu_data_parallel_opt_different_sized_ops=true '\
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'--xla_tpu_enable_async_collective_fusion=true '\
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'--xla_tpu_enable_async_collective_fusion_multiple_steps=true '\
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'--xla_tpu_overlap_compute_collective_tc=true '\
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'--xla_enable_async_all_gather=true '\
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'--xla_tpu_scoped_vmem_limit_kib=65536 '\
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'--xla_tpu_enable_async_all_to_all=true '\
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'--xla_tpu_enable_all_experimental_scheduler_features=true '\
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'--xla_tpu_enable_scheduler_memory_pressure_tracking=true '\
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'--xla_tpu_host_transfer_overlap_limit=24 '\
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'--xla_tpu_aggressive_opt_barrier_removal=ENABLED '\
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'--xla_lhs_prioritize_async_depth_over_stall=ENABLED '\
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'--xla_should_allow_loop_variant_parameter_in_chain=ENABLED '\
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'--xla_should_add_loop_invariant_op_in_chain=ENABLED '\
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'--xla_max_concurrent_host_send_recv=100 '\
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'--xla_tpu_scheduler_percent_shared_memory_limit=100 '\
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'--xla_latency_hiding_scheduler_rerun=2 '\
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'--xla_tpu_use_minor_sharding_for_major_trivial_input=true '\
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'--xla_tpu_relayout_group_size_threshold_for_reduce_scatter=1 '\
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'--xla_tpu_spmd_rng_bit_generator_unsafe=true '\
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'--xla_tpu_assign_all_reduce_scatter_layout=true'
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source "$VENV/bin/activate"
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export PYTHONPATH=$REPO_DIR/src:${PYTHONPATH:-}
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export HF_HOME=/dev/shm/maxdiffusion_cache/huggingface
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export HF_HUB_CACHE=/dev/shm/maxdiffusion_cache/huggingface/hub
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export HF_HUB_ENABLE_HF_TRANSFER=1
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export HF_HUB_OFFLINE=1
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export JAX_COMPILATION_CACHE_DIR=/dev/shm/maxdiffusion_cache/jax
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export XLA_CACHE_DIR=/dev/shm/maxdiffusion_cache/xla
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export TMPDIR=/dev/shm/maxdiffusion_cache/tmp
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# ── helper ────────────────────────────────────────────────────────────────────
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# For hybrid `ulysses_ring`, the 4th and 5th args are the ring and ulysses sizes
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# (which use dedicated mesh axes); context and tensor are pinned to 1.
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# For pure `ulysses` and `ring`, the 4th arg is context size and 5th is unused.
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run_case() {
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local run_name="$1"
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local attention="$2"
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local ici_dp="$3"
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local ici_a="$4" # context (pure) | ring (hybrid)
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local ici_b="$5" # unused (pure) | ulysses (hybrid)
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local results_dir="$RESULTS_ROOT/$run_name"
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rm -rf "$results_dir" "$OUTPUT_ROOT/$run_name"
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mkdir -p "$results_dir"
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rm -f /tmp/libtpu_lockfile
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mkdir -p "$TMPDIR"
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local ici_cp ici_tp ici_ring ici_ulysses
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if [[ "$attention" == "ulysses_ring" || "$attention" == "ulysses_tokamax_ring" ]]; then
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ici_cp=1; ici_tp=1; ici_ring="$ici_a"; ici_ulysses="$ici_b"
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echo "[$(date -u +%T)] ── Starting $run_name (attention=$attention dp=$ici_dp ring=$ici_ring ulysses=$ici_ulysses) ──"
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else
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ici_cp="$ici_a"; ici_tp=1; ici_ring=1; ici_ulysses=1
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echo "[$(date -u +%T)] ── Starting $run_name (attention=$attention dp=$ici_dp cp=$ici_cp) ──"
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fi
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local common_args="run_name=$run_name \
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attention=$attention \
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ici_data_parallelism=$ici_dp \
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ici_fsdp_parallelism=1 \
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ici_context_parallelism=$ici_cp \
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ici_tensor_parallelism=$ici_tp \
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ici_ring_parallelism=$ici_ring \
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ici_ulysses_parallelism=$ici_ulysses \
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dcn_data_parallelism=1 \
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dcn_fsdp_parallelism=1 \
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dcn_context_parallelism=1 \
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dcn_tensor_parallelism=1 \
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dcn_ring_parallelism=1 \
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dcn_ulysses_parallelism=1 \
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height=720 width=1280 num_frames=81 num_inference_steps=40 \
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per_device_batch_size=0.125 \
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output_dir=$OUTPUT_ROOT \
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scan_layers=True \
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write_metrics=False \
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write_timing_metrics=False \
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enable_profiler=True \
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skip_first_n_steps_for_profiler=5 \
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profiler_steps=10"
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# launch worker 1 in background via SSH
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local remote_cmd
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remote_cmd="$(printf '%q' "set -euo pipefail
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export LIBTPU_INIT_ARGS='$LIBTPU_INIT_ARGS'
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source $VENV/bin/activate
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export PYTHONPATH=$REPO_DIR/src:\${PYTHONPATH:-}
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export HF_HOME=$HF_HOME
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export HF_HUB_CACHE=$HF_HUB_CACHE
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export HF_HUB_ENABLE_HF_TRANSFER=1
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export HF_HUB_OFFLINE=1
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export JAX_COMPILATION_CACHE_DIR=$JAX_COMPILATION_CACHE_DIR
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export XLA_CACHE_DIR=$XLA_CACHE_DIR
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export TMPDIR=$TMPDIR
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rm -f /tmp/libtpu_lockfile
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mkdir -p $TMPDIR $results_dir $OUTPUT_ROOT
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cd $results_dir
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python -u $REPO_DIR/src/maxdiffusion/generate_wan.py $CONFIG $common_args 2>&1 | tee $results_dir/worker1.log")"
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/usr/bin/ssh $SSH_OPTS "$WORKER1_USER@$WORKER1_IP" "bash -lc $remote_cmd" &
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local remote_pid=$!
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cd "$results_dir"
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# Disable -e for the python call so a single run failing doesn't kill the whole sequence.
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set +e
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python -u "$REPO_DIR/src/maxdiffusion/generate_wan.py" \
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"$CONFIG" \
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$common_args \
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2>&1 | tee "$results_dir/worker0.log"
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local local_status=$?
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wait "$remote_pid"
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local remote_status=$?
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set -e
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echo "[$(date -u +%T)] $run_name done — local=$local_status remote=$remote_status"
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echo "────────────────────────────────────────────────────────────────────────"
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}
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# ── run matrix ────────────────────────────────────────────────────────────────
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# Pure runs: args = dp cp _ (cp on context axis)
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# Hybrid runs: args = dp ring ulysses (dedicated ring + ulysses axes)
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# run_name attention dp a b
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run_case ulysses_dp2_cp8 ulysses 2 8 1
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run_case ring_dp2_cp8 ring 2 8 1
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run_case ulysses_ring_dp2_cp8_4x2 ulysses_ring 2 4 2
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run_case ulysses_ring_dp2_cp8_2x4 ulysses_ring 2 2 4
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run_case ulysses_ring_dp1_cp16_4x4 ulysses_ring 1 4 4
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echo "[$(date -u +%T)] All benchmark runs complete."

‎docs/tpu_multihost_wan_bench.md‎

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# TPU Multihost WAN Benchmarks
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This note shows how to connect to a TPU v7x-16 multihost VM and run WAN attention comparisons on both workers.
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The examples below assume:
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- TPU name: `rish-tpu-7x16`
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- Zone: `europe-west2-a`
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- Project: `tpu-prod-env-one-vm`
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- Repo path on both workers: `/dev/shm/maxdiffusion`
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- Venv path on both workers: `/dev/shm/maxdiffusion/.venv-tpu`
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- HF cache path on both workers: `/dev/shm/maxdiffusion_cache/huggingface`
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For the current `rish-tpu-7x16` allocation, the worker endpoints resolved to:
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- worker 0: `sa_112155357684894056033@10.154.0.62`
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- worker 1: `sa_112155357684894056033@10.154.0.59`
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- worker 0 host key alias: `tpu.2884514015978940116-0-IE5JIi`
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- worker 1 host key alias: `tpu.2884514015978940116-1-jgVFrB`
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## Connect
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Set the project and zone:
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```bash
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gcloud config set project tpu-prod-env-one-vm
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gcloud config set compute/zone europe-west2-a
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```
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Check that both workers are reachable:
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```bash
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gcloud alpha compute tpus tpu-vm ssh rish-tpu-7x16 \
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--worker=all \
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--internal-ip \
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--zone=europe-west2-a \
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--quiet \
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--command='hostname'
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```
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Print the raw ssh command for a single worker when you need it:
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```bash
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gcloud alpha compute tpus tpu-vm ssh rish-tpu-7x16 \
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--worker=0 \
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--internal-ip \
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--zone=europe-west2-a \
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--dry-run
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```
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## Stage Code On Worker 1
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If worker 0 already has the repo, venv, and WAN checkpoint cache, mirror them to worker 1 from worker 0:
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```bash
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rsync -a --delete \
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--exclude='.git' \
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--exclude='.venv' \
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--exclude='.venv-tpu' \
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--exclude='__pycache__' \
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--exclude='*.pyc' \
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-e 'ssh -T -i ~/.ssh/google_compute_engine -o CheckHostIP=no -o HashKnownHosts=no -o HostKeyAlias=tpu.2884514015978940116-1-jgVFrB -o IdentitiesOnly=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=~/.ssh/google_compute_known_hosts' \
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/dev/shm/maxdiffusion/ \
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sa_112155357684894056033@10.154.0.59:/dev/shm/maxdiffusion/
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```
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```bash
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rsync -a --delete \
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-e 'ssh -T -i ~/.ssh/google_compute_engine -o CheckHostIP=no -o HashKnownHosts=no -o HostKeyAlias=tpu.2884514015978940116-1-jgVFrB -o IdentitiesOnly=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=~/.ssh/google_compute_known_hosts' \
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/dev/shm/maxdiffusion/.venv-tpu/ \
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sa_112155357684894056033@10.154.0.59:/dev/shm/maxdiffusion/.venv-tpu/
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```
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```bash
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rsync -a --partial --delete \
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-e 'ssh -T -i ~/.ssh/google_compute_engine -o CheckHostIP=no -o HashKnownHosts=no -o HostKeyAlias=tpu.2884514015978940116-1-jgVFrB -o IdentitiesOnly=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=~/.ssh/google_compute_known_hosts' \
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/dev/shm/maxdiffusion_cache/huggingface/hub/models--Wan-AI--Wan2.2-T2V-A14B-Diffusers/ \
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sa_112155357684894056033@10.154.0.59:/dev/shm/maxdiffusion_cache/huggingface/hub/models--Wan-AI--Wan2.2-T2V-A14B-Diffusers/
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```
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## Smoke Test
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Run a multihost JAX initialization smoke test on both workers:
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```bash
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gcloud alpha compute tpus tpu-vm ssh rish-tpu-7x16 \
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--worker=all \
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--internal-ip \
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--zone=europe-west2-a \
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--quiet \
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--command='
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set -e
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source /dev/shm/maxdiffusion/.venv-tpu/bin/activate
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export PYTHONPATH=/dev/shm/maxdiffusion/src:${PYTHONPATH}
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python - <<'"'"'PY'"'"'
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import socket
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import jax
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jax.distributed.initialize()
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print(
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f"host={socket.gethostname()} "
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f"process_index={jax.process_index()} "
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f"process_count={jax.process_count()} "
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f"local_device_count={jax.local_device_count()} "
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f"device_count={jax.device_count()}"
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)
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PY'
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```
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## Run WAN Comparison Jobs
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All commands below use:
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- model config: `src/maxdiffusion/configs/base_wan_27b.yml`
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- checkpoint: `Wan-AI/Wan2.2-T2V-A14B-Diffusers`
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- global batch size: `2`
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- per-device batch size: `0.125`
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- total devices: `16`
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Common environment:
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```bash
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export REPO_DIR=/dev/shm/maxdiffusion
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export VENV=/dev/shm/maxdiffusion/.venv-tpu
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export HF_HOME=/dev/shm/maxdiffusion_cache/huggingface
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export HF_HUB_CACHE=/dev/shm/maxdiffusion_cache/huggingface/hub
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export HF_HUB_ENABLE_HF_TRANSFER=1
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export JAX_COMPILATION_CACHE_DIR=/dev/shm/maxdiffusion_cache/jax
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export XLA_CACHE_DIR=/dev/shm/maxdiffusion_cache/xla
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export TMPDIR=/dev/shm/maxdiffusion_cache/tmp
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export RESULTS_ROOT=/dev/shm/maxdiffusion/bench_results
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export CONFIG=$REPO_DIR/src/maxdiffusion/configs/base_wan_27b.yml
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export COMMON_ARGS='height=720 width=1280 num_frames=81 num_inference_steps=40 per_device_batch_size=0.125 output_dir=/dev/shm/maxdiffusion/bench_outputs scan_layers=True enable_profiler=False'
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```
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Helper to run one job on both workers:
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```bash
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run_case() {
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local run_name="$1"
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local attention="$2"
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local ici_dp="$3"
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local ici_cp="$4"
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local ici_tp="$5"
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gcloud alpha compute tpus tpu-vm ssh rish-tpu-7x16 \
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--worker=all \
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--internal-ip \
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--zone=europe-west2-a \
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--quiet \
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--command="
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set -e
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source $VENV/bin/activate
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export PYTHONPATH=$REPO_DIR/src:\${PYTHONPATH}
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export HF_HOME=$HF_HOME
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export HF_HUB_CACHE=$HF_HUB_CACHE
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export HF_HUB_ENABLE_HF_TRANSFER=$HF_HUB_ENABLE_HF_TRANSFER
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export JAX_COMPILATION_CACHE_DIR=$JAX_COMPILATION_CACHE_DIR
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export XLA_CACHE_DIR=$XLA_CACHE_DIR
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export TMPDIR=$TMPDIR
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mkdir -p $RESULTS_ROOT /dev/shm/maxdiffusion/bench_outputs
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cd $RESULTS_ROOT
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python $REPO_DIR/src/maxdiffusion/generate_wan.py \
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$CONFIG \
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run_name=$run_name \
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attention=$attention \
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ici_data_parallelism=$ici_dp \
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ici_fsdp_parallelism=1 \
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ici_context_parallelism=$ici_cp \
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ici_tensor_parallelism=$ici_tp \
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dcn_data_parallelism=1 \
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dcn_fsdp_parallelism=1 \
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dcn_context_parallelism=1 \
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dcn_tensor_parallelism=1 \
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$COMMON_ARGS \
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2>&1 | tee $RESULTS_ROOT/$run_name.\$(hostname).log
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"
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}
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```
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Run matrix:
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```bash
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run_case ulysses_dp2_cp8 ulysses 2 8 1
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run_case ring_dp2_cp8 ring 2 8 1
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run_case ulysses_ring_dp2_cp8_2x4 ulysses_ring 2 2 4
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run_case ulysses_ring_dp2_cp8_4x2 ulysses_ring 2 4 2
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run_case ulysses_ring_dp1_cp16_4x4 ulysses_ring 1 4 4
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```
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## Topology Note
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TPU v7x exposes dual chiplets as two JAX devices. For `ulysses_ring`, keep the dual-chip pairing inside the Ulysses group by setting `ici_tensor_parallelism >= 2`.
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That means:
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- `2x4` uses tensor `4`, so the dual-chip pairing is inside the Ulysses side.
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- `4x2` uses tensor `2`, so the dual-chip pairing is still inside the Ulysses side.
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- `4x4` uses tensor `4`, so the dual-chip pairing is still inside the Ulysses side.
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The plain `ring` baseline has no Ulysses group, so it cannot preserve that property by construction.
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## Read Results
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Pull the timing summary from the per-host logs:
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```bash
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rg -n "compile_time:|generation_time:|generation time per video:|TIMING SUMMARY" /dev/shm/maxdiffusion/bench_results/*.log
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```
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If you want a single run's logs from both workers:
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```bash
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ls -1 /dev/shm/maxdiffusion/bench_results/ulysses_ring_dp2_cp8_2x4.*
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```

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