[ROCm][PERF] Enable AITER PA gluon decode for MiniMax-M3 MTP and dense layers - #52849
[ROCm][PERF] Enable AITER PA gluon decode for MiniMax-M3 MTP and dense layers#52849ukannika wants to merge 5 commits into
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Signed-off-by: ukannika <uma.kannikanti@amd.com>
Signed-off-by: ykamiset <yaminipreethi.kamisetty@amd.com>
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minor q @ukannika can you include your env vars for AITER, shuffle KV cache, etc. in the repro command above? |
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LGTM but cc @tjtanaa for the ROCM_AITER_FA changes/ @jhu960213 for the kv cache layout
Signed-off-by: ykamiset <yaminipreethi.kamisetty@amd.com>
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hey @ukannika Can you check pre-commit locally really quick? I know it's not running here, but I think there may be some errors |
checking now. thank you for reviewing. |
Sorry for that. we missed to push some code change. Fixed now. Thank you |
| raise ValueError("Block size must be a multiple of 16.") | ||
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| if rocm_aiter_ops.is_shuffle_kv_cache_enabled(): | ||
| return (num_blocks, 2, block_size, num_kv_heads, head_size) |
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Should we update this?
get_kv_cache_shape is used by gpu runner to determine how the kvcache is packed in the kvcache buffers/pool/management system. It is not referring to the kvcache shape expect by the kernels.
The KVCACHE is reshaped on the fly in the attention forward pass from (num_blocks, num_kv_heads, block_size, 2 * head_size) to (num_blocks, 2, block_size, num_kv_heads, head_size) every time.
num_blocks, block_size, num_kv_heads, _ = key_cache.shape
x = 16 // key_cache.element_size()
new_key_cache = key_cache.reshape(
num_blocks, num_kv_heads, head_size // x, block_size, x
)
new_value_cache = value_cache.reshape(
num_blocks, num_kv_heads, block_size // x, head_size, x
)
However, the kvcache stored in the kvcache management system is still (num_blocks, num_kv_heads, block_size, 2 * head_size)
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@tjtanaa we see an issue if we don't define the shape and stride order when the shuffle layout is enabled: the pool is then labeled (num_blocks, num_kv_heads, block_size, 2*head_size), where each tokens K is immediately followed by its own V, head_size elements apart. The cache write kernel still writes each blocks K in the shuffle layout because of shuffle layout flag enabled, which assumes K and V are kept apart. Looking into how is it working with shuffle layout enabled for asm pa kernel before this change.
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@tjtanaa Enabled the shuffle layout flag and tested the Llama2 70B model using the asm_pa code path. I am seeing an accuracy issue, and the current state of this file is broken due to the layout changes introduced in this PR #44455. AITER assembly paged-attention kernels require independently contiguous K and V storage. This PR addresses the accuracy issue as well.
Here's the command to reproduce accuracy issue
export VLLM_ROCM_USE_AITER=1
export VLLM_ROCM_SHUFFLE_KV_CACHE_LAYOUT=1
vllm serve /model/llama2-70b-chat-hf/fp4_quantized_gptq \
--dtype bfloat16 \
--quantization quark \
--tensor-parallel-size 1 \
--max-model-len 2048 \
--gpu-memory-utilization 0.94 \
--attention-backend ROCM_AITER_FA \
--kv-cache-dtype fp8 \
--block-size 16 \
--max-num-batched-tokens 32768 \
--max-num-seqs 6400 \
--enable-chunked-prefill \
--async-scheduling \
--host 0.0.0.0 \
--port 8000
curl -s http://127.0.0.1:8000/v1/completions -H "Content-Type: application/json" -d '{
"model": "/model/llama2-70b-chat-hf/fp4_quantized_gptq",
"prompt": "The capital of France is",
"max_tokens": 32,
"temperature": 0
}'```
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5 participants
Purpose
The gluon paged-attention decode kernel handles multi-token query lengths, so
EAGLE3 speculative decoding no longer has to fall back to native vllm unified_attention.
Test Plan
Server cmd to run EAGLE3 speculative decoding
Test Result
MiniMax-M3 with EAGLE3 3-token speculative decoding sees a significant uplift at long context: the AITER gluon paged-attention kernel replaces the unified_attention fallback and is substantially faster for longer contexts.
Accuracy score: