83 lines
2.7 KiB
Plaintext
83 lines
2.7 KiB
Plaintext
#include "attn_paged_decode_split_kv.cuh"
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#ifndef ASTRAI_NO_MMA
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#include "attn_paged_decode_split_kv_mma.cuh"
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#endif
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#include "attn_entry_utils.cuh"
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static void launch_paged_scalar_decode(PagedAttentionParams<bf16>& p) {
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int group_size = p.q_head / p.kv_head;
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int chunks_total = (p.kv_len + PDC_CHUNK - 1) / PDC_CHUNK;
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p.num_splits = compute_num_splits(p.batch * p.kv_head, chunks_total);
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alloc_split_partials(p);
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size_t smem = PDC_CHUNK * p.head_dim * sizeof(bf16);
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dim3 grid = dim3(p.batch * p.kv_head, 1, p.num_splits);
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dim3 block = dim3(32, group_size);
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paged_attn_decode_split_kv_kernel<<<grid, block, smem>>>(p);
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paged_attn_decode_combine_kernel<<<p.batch * p.q_head, p.head_dim>>>(p);
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}
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#ifndef ASTRAI_NO_MMA
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template <int HEAD_DIM, int BC, int STAGES = (HEAD_DIM <= 128) ? 2 : 1>
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static void launch_paged_mma_decode(PagedAttentionParams<bf16>& p) {
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int tiles_total = (p.kv_len + BC - 1) / BC;
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p.num_splits = compute_num_splits(p.batch * p.kv_head, tiles_total);
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alloc_split_partials(p);
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paged_attn_decode_split_kv_mma_kernel<HEAD_DIM, BC, STAGES><<<dim3(p.kv_head, p.batch, p.num_splits), 32>>>(p);
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paged_attn_decode_combine_kernel<<<p.batch * p.q_head, p.head_dim>>>(p);
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}
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#endif
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template <int HEAD_DIM>
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static void dispatch_paged_decode(PagedAttentionParams<bf16>& p) {
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#ifndef ASTRAI_NO_MMA
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int G = p.q_head / p.kv_head;
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if (!p.use_mask && G >= 1 && G <= 16 && p.page_size >= 32) {
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launch_paged_mma_decode<HEAD_DIM, 32>(p);
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return;
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}
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#endif
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launch_paged_scalar_decode(p);
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}
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torch::Tensor attn_paged_decode(
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torch::Tensor q,
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torch::Tensor page_table,
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torch::Tensor k_cache,
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torch::Tensor v_cache,
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int64_t page_size,
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int64_t kv_len,
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c10::optional<torch::Tensor> mask,
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int64_t causal_offset,
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double scale,
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int64_t layout
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) {
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PagedAttentionParams<bf16> p;
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attn_pack_paged_params(q, page_table, k_cache, v_cache,
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page_size, kv_len, mask, causal_offset, scale, layout, p);
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auto O = torch::empty_strided(q.sizes(), q.strides(), q.options());
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auto O_view = (layout == 1) ? O.transpose(1, 2) : O;
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p.o = (bf16*)O_view.data_ptr();
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dispatch_head_dim(p.head_dim, [&]<int D>() { dispatch_paged_decode<D>(p); });
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return O;
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}
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
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m.def("attn_paged_decode", &attn_paged_decode,
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py::arg("q"),
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py::arg("page_table"),
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py::arg("k_cache"),
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py::arg("v_cache"),
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py::arg("page_size"),
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py::arg("kv_len"),
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py::arg("mask") = py::none(),
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py::arg("causal_offset") = -1,
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py::arg("scale") = 0.0,
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py::arg("layout") = 0,
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"Paged GQA decode — split-KV with direct page-table access.");
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}
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