GQA paged decode h6 kv1 d128 ps64
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gqa-paged-attention
Batched Grouped Query Attention decode with a paged KV cache (page_size=64). Captured from MiniMax M2 with tensor parallel size 8 (48/8=6 q-heads, 8/8=1 kv-head).
Current records
No published measurement for the selected workload.
Implementations
Implementation
Runtime
Best latency
Evidence
Availability
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]
kv_last_page_lenint32 [batch_size]
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 = 64
batch_sizevariable
len_indptrvariable
num_kv_headsconstant = 1
num_qo_headsconstant = 6
num_kv_indicesvariable
determinismunspecified
constraintsNo mutation or aliasing
Identity
No source imports for this operation yet.How records are decidedJSON