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GQA paged decode h48 kv8 d128 ps1

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gqa-paged-attention

Batched Grouped Query Attention decode with a paged KV cache (page_size=1). Captured from Mixtral 8x22B. 48 q-heads, 8 kv-heads, head_dim=128.

Current records

No published measurement for the selected workload.

Implementations

Implementation
Runtime
Best latency
Evidence
Availability
flashinfer_wrapper_925784FlashInfer-Bench baselines
python
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Apache-2.0 · source

Semantics

Inputs and outputs
qbf16 [batch_size, num_qo_heads, head_dim]
k_cachebf16 [num_pages, page_size, num_kv_heads, head_dim]
v_cachebf16 [num_pages, page_size, num_kv_heads, head_dim]
kv_indptrint32 [len_indptr]
kv_indicesint32 [num_kv_indices]
sm_scalefp32 scalar
outputbf16 [batch_size, num_qo_heads, head_dim]
lsefp32 [batch_size, num_qo_heads]
Axes and behavior
head_dimconstant = 128
num_pagesvariable
page_sizeconstant = 1
batch_sizevariable
len_indptrvariable
num_kv_headsconstant = 8
num_qo_headsconstant = 48
num_kv_indicesvariable
determinismunspecified
constraintsNo mutation or aliasing
Identity
aliasgqa_paged_decode_h48_kv8_d128_ps1modelmixtral-8x22bsha2567aede65bea7e…
No source imports for this operation yet.How records are decidedJSON