perf: precompute ragged Q tile scheduling

This commit is contained in:
2026-08-16 23:32:46 +08:00
parent 0d0dc64884
commit 1bcd8f53ab
17 changed files with 283 additions and 141 deletions
+4 -1
View File
@@ -13,7 +13,7 @@ enum TensorLayout : int {
// - Contiguous K/V: dense [batch, kv_head, kv_len, head_dim] tensors (k/v).
// - Paged (SGLang-style): flat pool [size, kv_head, head_dim] + req_to_token.
// Each kernel selects the addressing via a KVSource policy (see
// attn_kv_source.cuh); a given call only touches the fields of one mode, so
// attn_layout_policies.cuh); a given call only touches the fields of one mode, so
// this is a POD shared by both paths rather than two parallel structs that
// drift out of sync.
template<typename T, typename AT = float>
@@ -59,6 +59,9 @@ struct AttentionParams {
const int* __restrict__ req_pool_indices; // [batch]
const int* __restrict__ kv_indptr; // [batch + 1]
const int* __restrict__ qo_indptr; // [batch + 1] or nullptr for decode
const int* __restrict__ q_tile_to_batch; // [num_q_tiles], prefill only
const int* __restrict__ q_tile_to_index; // [num_q_tiles], prefill only
int num_q_tiles;
int max_context_len; // req_to_token stride (dim 1)
// Decode split-KV workspace