Files
vllm/benchmarks/attention_benchmarks/configs/mla_decode.yaml
Matthew Bonanni e82fa448c4 Add attention benchmarking tools (#26835)
Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>
Co-authored-by: Claude <noreply@anthropic.com>
2026-01-28 00:09:20 +00:00

62 lines
1.5 KiB
YAML

# MLA decode-only benchmark configuration
model:
name: "deepseek-v3"
num_layers: 60
num_q_heads: 128
num_kv_heads: 1 # MLA uses single latent KV
head_dim: 576
kv_lora_rank: 512
qk_nope_head_dim: 128
qk_rope_head_dim: 64
v_head_dim: 128
block_size: 128 # CUTLASS MLA and FlashAttn MLA use 128
batch_specs:
# Small batches, varying sequence lengths
- "16q1s512" # 16 requests, 512 KV cache
- "16q1s1k" # 16 requests, 1k KV cache
- "16q1s2k" # 16 requests, 2k KV cache
- "16q1s4k" # 16 requests, 4k KV cache
# Medium batches
- "32q1s1k" # 32 requests, 1k KV cache
- "32q1s2k" # 32 requests, 2k KV cache
- "32q1s4k" # 32 requests, 4k KV cache
- "32q1s8k" # 32 requests, 8k KV cache
# Large batches
- "64q1s1k" # 64 requests, 1k KV cache
- "64q1s2k" # 64 requests, 2k KV cache
- "64q1s4k" # 64 requests, 4k KV cache
- "64q1s8k" # 64 requests, 8k KV cache
# Very large batches
- "128q1s1k" # 128 requests, 1k KV cache
- "128q1s2k" # 128 requests, 2k KV cache
# Long context
- "32q1s16k" # 32 requests, 16k KV cache
- "32q1s32k" # 32 requests, 32k KV cache
backends:
- cutlass_mla
- flashinfer_mla
- flashattn_mla # Hopper only
- flashmla # Hopper only
device: "cuda:0"
repeats: 5
warmup_iters: 3
profile_memory: true
# Backend-specific tuning
cutlass_mla:
num_kv_splits: auto # or specific value like 4, 8, 16
flashattn_mla:
reorder_batch_threshold: 512
flashmla:
reorder_batch_threshold: 1