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refactor: extract shared dispatcher header, unify MMA/scalar dispatch format

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- Merge 3 duplicated dispatch blocks into single attn_dispatchers.cuh
- Merge compute_num_splits from attn_utils.cuh into dispatcher header
- All dim3 grid/block declarations and <<<>>> launches are single-line
- Production .cu files (35-42 loc) only handle torch wrapping + pybind11
- Test files include dispatcher header directly, removing all #ifndef ASTRAI_NO_MMA duplication
This commit is contained in:
ViperEkura
2026-07-21 22:21:39 +08:00
parent a01e8bbe98
commit f7a16efc9d
9 changed files with 245 additions and 406 deletions
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csrc/tests/attn_paged_decode_test.cu
+19 -77
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@@ -5,12 +5,8 @@
#include <cstring>
#include "test_utils.cuh"
#include "../kernels/attn_paged_decode_split_kv.cuh"
#ifndef ASTRAI_NO_MMA
#include "../kernels/attn_paged_decode_split_kv_mma.cuh"
#endif
#include "../kernels/attn_dispatchers.cuh"
// Copy contiguous K/V from page pool (reference gather)
static void gather_kv_cpu(
const bf16* h_k_pool, const bf16* h_v_pool,
const int64_t* h_pt, int B, int Hkv, int kv_len,
@@ -28,7 +24,8 @@ static void gather_kv_cpu(
size_t src_base = (size_t)phys * page_stride
+ (size_t)pg_off * Hkv * head_dim
+ h * head_dim;
size_t dst_base = ((size_t)b * Hkv + h) * kv_len * head_dim + (size_t)pos * head_dim;
size_t dst_base = ((size_t)b * Hkv + h) * kv_len * head_dim
+ (size_t)pos * head_dim;
memcpy(h_k + dst_base, h_k_pool + src_base, head_dim * sizeof(bf16));
memcpy(h_v + dst_base, h_v_pool + src_base, head_dim * sizeof(bf16));
}
@@ -36,59 +33,6 @@ static void gather_kv_cpu(
}
}
#ifndef ASTRAI_NO_MMA
template <int HEAD_DIM, bool IsCausal, bool HasMask>
static void launch_paged_mma_decode(PagedAttentionParams<bf16, float>& p) {
constexpr int STAGES = (HEAD_DIM <= 128) ? 2 : 1;
using Traits = KernelTraits<HEAD_DIM, 32, 1, STAGES>;
int tiles_total = (p.kv_len + 32 - 1) / 32;
p.num_splits = compute_num_splits(p.batch * p.kv_head, tiles_total);
paged_attn_decode_split_kv_mma_kernel<Traits, IsCausal, HasMask>
<<<dim3(p.kv_head, p.batch, p.num_splits), 32>>>(p);
}
#endif
template <int HEAD_DIM, bool IsCausal, bool HasMask>
static void launch_paged_scalar_decode(PagedAttentionParams<bf16, float>& p) {
int group_sz = p.q_head / p.kv_head;
int chunks_total = (p.kv_len + PDC_CHUNK - 1) / PDC_CHUNK;
p.num_splits = compute_num_splits(p.batch * p.kv_head, chunks_total);
size_t smem = PDC_CHUNK * p.head_dim * sizeof(bf16);
paged_attn_decode_split_kv_kernel<HEAD_DIM, IsCausal, HasMask><<<
dim3(p.batch * p.kv_head, 1, p.num_splits),
dim3(32, group_sz), smem>>>(p);
}
template <int HEAD_DIM>
static void launch_paged_decode(PagedAttentionParams<bf16, float>& p) {
bool is_causal = (p.causal_offset >= 0);
bool has_mask = (p.use_mask && p.mask);
#ifndef ASTRAI_NO_MMA
int G_check = p.q_head / p.kv_head;
bool use_mma = G_check >= 1 && G_check <= 16 && p.page_size >= 32;
if (use_mma) {
if (is_causal) {
if (has_mask) launch_paged_mma_decode<HEAD_DIM, true, true>(p);
else launch_paged_mma_decode<HEAD_DIM, true, false>(p);
} else {
if (has_mask) launch_paged_mma_decode<HEAD_DIM, false, true>(p);
else launch_paged_mma_decode<HEAD_DIM, false, false>(p);
}
} else
#endif
{
if (is_causal) {
if (has_mask) launch_paged_scalar_decode<HEAD_DIM, true, true>(p);
else launch_paged_scalar_decode<HEAD_DIM, true, false>(p);
} else {
if (has_mask) launch_paged_scalar_decode<HEAD_DIM, false, true>(p);
else launch_paged_scalar_decode<HEAD_DIM, false, false>(p);
}
}
paged_attn_decode_combine_kernel<<<p.batch * p.q_head, p.head_dim>>>(p);
}
template <int HEAD_DIM>
static int run_test(int B, int Hq, int Hkv, int kv_len, int page_size, int causal, int seed) {
printf("B=%d Hq=%d Hkv=%d kv_len=%d page_sz=%d head_dim=%d causal=%d ... ",
@@ -97,23 +41,22 @@ static int run_test(int B, int Hq, int Hkv, int kv_len, int page_size, int causa
int max_pages = (kv_len + page_size - 1) / page_size;
int n_phys_pages = B * max_pages;
int max_splits = 32;
size_t sz_q = (size_t)B * Hq * 1 * HEAD_DIM * sizeof(bf16);
size_t sz_o = sz_q;
size_t sz_kv = (size_t)n_phys_pages * page_size * Hkv * HEAD_DIM * sizeof(bf16);
size_t sz_pt = (size_t)B * max_pages * sizeof(int64_t);
int max_splits = 32;
size_t sz_op = (size_t)B * Hq * max_splits * HEAD_DIM * sizeof(float);
size_t sz_ml = (size_t)B * Hq * max_splits * 2 * sizeof(float);
bf16 *d_q, *d_o_paged, *d_o_ref;
bf16 *d_q, *d_o_paged;
bf16 *d_k_pool, *d_v_pool;
int64_t* d_pt;
float *d_op, *d_ml;
cudaMalloc(&d_q, sz_q);
cudaMalloc(&d_o_paged, sz_o);
cudaMalloc(&d_o_ref, sz_o);
cudaMalloc(&d_k_pool, sz_kv);
cudaMalloc(&d_v_pool, sz_kv);
cudaMalloc(&d_pt, sz_pt);
@@ -136,7 +79,8 @@ static int run_test(int B, int Hq, int Hkv, int kv_len, int page_size, int causa
for (int h = 0; h < Hkv; h++) {
for (int d = 0; d < HEAD_DIM; d++) {
float v = sinf((float)(pg * 7919 + off * 1049 + h * 331 + d));
size_t idx = (size_t)pg * ps + (size_t)off * Hkv * HEAD_DIM + h * HEAD_DIM + d;
size_t idx = (size_t)pg * ps + (size_t)off * Hkv * HEAD_DIM
+ h * HEAD_DIM + d;
h_k_pool[idx] = __float2bfloat16(v);
h_v_pool[idx] = __float2bfloat16(v * 0.3f);
}
@@ -170,20 +114,19 @@ static int run_test(int B, int Hq, int Hkv, int kv_len, int page_size, int causa
cpu_attention_ref(h_q_f, h_k_f, h_v_f, nullptr, h_o_ref, B, Hq, Hkv,
1, kv_len, HEAD_DIM, causal ? 0 : -1);
float scale_val = 1.0f / sqrtf((float)HEAD_DIM);
PagedAttentionParams<bf16, float> p;
PagedAttentionParams<bf16> p;
p.batch = B; p.q_head = Hq; p.kv_head = Hkv; p.q_len = 1;
p.kv_len = kv_len; p.head_dim = HEAD_DIM;
p.use_mask = 0; p.causal_offset = causal ? 0 : -1;
set_default_paged_strides(p);
p.num_splits = 1; p.scale = scale_val;
p.scale = 1.0f / sqrtf((float)HEAD_DIM);
p.page_size = page_size; p.max_pages = max_pages;
p.page_table = d_pt;
p.k_cache = d_k_pool; p.v_cache = d_v_pool;
p.q = d_q; p.mask = nullptr; p.o = d_o_paged;
p.o_part = d_op; p.ml_part = d_ml;
launch_paged_decode<HEAD_DIM>(p);
dispatch_by_head_dim(HEAD_DIM, [&]<int H>() { dispatch_paged_decode<H>(p); });
cudaDeviceSynchronize();
bf16* h_o_bf16 = (bf16*)malloc(sz_o);
@@ -222,7 +165,7 @@ static int run_test(int B, int Hq, int Hkv, int kv_len, int page_size, int causa
free(h_k_cont); free(h_v_cont);
free(h_q_f); free(h_k_f); free(h_v_f);
free(h_o_ref); free(h_o_bf16); free(h_o_paged);
cudaFree(d_q); cudaFree(d_o_paged); cudaFree(d_o_ref);
cudaFree(d_q); cudaFree(d_o_paged);
cudaFree(d_k_pool); cudaFree(d_v_pool); cudaFree(d_pt);
cudaFree(d_op); cudaFree(d_ml);
@@ -248,28 +191,26 @@ static const TestCase TESTS[] = {
{128, 2, 32, 8, 512, 128, 0, 11},
{128, 1, 16, 2, 256, 128, 0, 12},
{128, 2, 32, 4, 512, 128, 0, 13},
{128, 2, 8, 2, 128, 128, 1, 14}, // causal paged decode
{128, 2, 8, 2, 128, 128, 1, 14}, // causal
};
static int dispatch_test(const TestCase& tc) {
bool matched = false;
int r = 0;
dispatch_by_head_dim(tc.head_dim, [&]<int D>() {
matched = true;
r = run_test<D>(tc.B, tc.Hq, tc.Hkv, tc.kv_len, tc.page_size, tc.causal, tc.seed);
});
return matched ? r : 1;
return r;
}
template <int HEAD_DIM>
static void bench_config(int B, int Hq, int Hkv, int kv_len, int page_size) {
int max_pages = (kv_len + page_size - 1) / page_size;
int n_phys_pages = B * max_pages;
int max_splits = 32;
size_t sz_q = (size_t)B * Hq * 1 * HEAD_DIM * sizeof(bf16);
size_t sz_kv = (size_t)n_phys_pages * page_size * Hkv * HEAD_DIM * sizeof(bf16);
size_t sz_pt = (size_t)B * max_pages * sizeof(int64_t);
int max_splits = 32;
size_t sz_op = (size_t)B * Hq * max_splits * HEAD_DIM * sizeof(float);
size_t sz_ml = (size_t)B * Hq * max_splits * 2 * sizeof(float);
@@ -296,13 +237,12 @@ static void bench_config(int B, int Hq, int Hkv, int kv_len, int page_size) {
cudaMemcpy(d_pt, h_pt, sz_pt, cudaMemcpyHostToDevice);
free(h_pt);
float scale_val = 1.0f / sqrtf((float)HEAD_DIM);
PagedAttentionParams<bf16, float> pa;
PagedAttentionParams<bf16> pa;
pa.batch = B; pa.q_head = Hq; pa.kv_head = Hkv; pa.q_len = 1;
pa.kv_len = kv_len; pa.head_dim = HEAD_DIM;
pa.use_mask = 0; pa.causal_offset = -1;
set_default_paged_strides(pa);
pa.num_splits = 1; pa.scale = scale_val;
pa.scale = 1.0f / sqrtf((float)HEAD_DIM);
pa.page_size = page_size; pa.max_pages = max_pages;
pa.page_table = d_pt;
pa.k_cache = d_k_pool; pa.v_cache = d_v_pool;
@@ -310,7 +250,9 @@ static void bench_config(int B, int Hq, int Hkv, int kv_len, int page_size) {
pa.o_part = d_op; pa.ml_part = d_ml;
const int WARMUP = 10, ITERS = 100;
auto launch = [&]() { launch_paged_decode<HEAD_DIM>(pa); };
auto launch = [&]() {
dispatch_by_head_dim(HEAD_DIM, [&]<int H>() { dispatch_paged_decode<H>(pa); });
};
double flops = 4.0 * B * Hq * (double)kv_len * HEAD_DIM;
size_t nKV = (size_t)B * Hkv * kv_len * HEAD_DIM;
double bytes = 2.0 * (2.0 * nKV * sizeof(bf16));