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vllm/benchmarks/attention_benchmarks/configs/mla_sparse_prefill.yaml
Matthew Bonanni f444c05c32 [Attention] Use FA4 for MLA prefill (#34732)
Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>
2026-03-12 12:10:17 -04:00

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YAML

# MLA prefill-only benchmark configuration for sparse backends
model:
name: "deepseek-v3"
num_layers: 60
num_q_heads: 128
num_kv_heads: 1
head_dim: 576
kv_lora_rank: 512
qk_nope_head_dim: 128
qk_rope_head_dim: 64
v_head_dim: 128
block_size: 128
# Model parameter sweep: simulate tensor parallelism by varying num_q_heads
# TP=1: 128 heads, TP=2: 64 heads, TP=4: 32 heads, TP=8: 16 heads
model_parameter_sweep:
param_name: "num_q_heads"
values: [128, 64, 32, 16]
label_format: "{backend}_{value}h"
batch_specs:
# Pure prefill
- "1q512"
- "1q1k"
- "1q2k"
- "1q4k"
- "1q8k"
# Batched pure prefill
- "2q512"
- "2q1k"
- "2q2k"
- "2q4k"
- "2q8k"
- "4q512"
- "4q1k"
- "4q2k"
- "4q4k"
- "4q8k"
- "8q512"
- "8q1k"
- "8q2k"
- "8q4k"
- "8q8k"
# Extend
- "1q512s4k"
- "1q512s8k"
- "1q1ks8k"
- "1q2ks8k"
- "1q2ks16k"
- "1q4ks16k"
backends:
- FLASHMLA_SPARSE
- FLASHINFER_MLA_SPARSE
device: "cuda:0"
repeats: 10
warmup_iters: 3
profile_memory: true