fix: stabilize paged decode attention kernels

- zero-fill split partials so combine skips unwritten splits deterministically
- skip loading masked KV in paged decode kernels to avoid 0*NaN output poisoning
- zero-fill shared memory tile buffers to prevent stale NaN leaking into softmax
This commit is contained in:
2026-07-31 21:01:12 +08:00
parent 7aa5ed09d9
commit 21ddead238
3 changed files with 23 additions and 5 deletions
+3 -2
View File
@@ -1,4 +1,5 @@
#pragma once #pragma once
#include <float.h>
#include <torch/extension.h> #include <torch/extension.h>
#include <c10/cuda/CUDAGuard.h> #include <c10/cuda/CUDAGuard.h>
#include "attn_common.h" #include "attn_common.h"
@@ -23,8 +24,8 @@ using bf16 = __nv_bfloat16;
template<typename P> template<typename P>
inline void alloc_split_partials(P& p) { inline void alloc_split_partials(P& p) {
auto fopt = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA); auto fopt = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
auto o_part = torch::empty(at::IntArrayRef{p.batch, p.q_head, MAX_SPLITS, p.head_dim}, fopt); auto o_part = torch::zeros(at::IntArrayRef{p.batch, p.q_head, MAX_SPLITS, p.head_dim}, fopt);
auto ml_part = torch::empty(at::IntArrayRef{p.batch, p.q_head, MAX_SPLITS, 2}, fopt); auto ml_part = torch::full(at::IntArrayRef{p.batch, p.q_head, MAX_SPLITS, 2}, -FLT_MAX, fopt);
p.o_part = (float*)o_part.data_ptr(); p.o_part = (float*)o_part.data_ptr();
p.ml_part = (float*)ml_part.data_ptr(); p.ml_part = (float*)ml_part.data_ptr();
} }
+10 -3
View File
@@ -67,14 +67,17 @@ __global__ void paged_attn_decode_split_kv_kernel(PagedAttentionParams<bf16> p)
partial = warp_reduce_sum(partial) * p.scale; partial = warp_reduce_sum(partial) * p.scale;
int kv_idx = chunk_start + s; int kv_idx = chunk_start + s;
bool masked = false;
if constexpr (HasMask) { if constexpr (HasMask) {
if (!p.mask[mask_base + kv_idx]) if (!p.mask[mask_base + kv_idx])
partial = -FLT_MAX; masked = true;
} }
if constexpr (IsCausal) { if constexpr (IsCausal) {
if (kv_idx > p.causal_offset) if (kv_idx > p.causal_offset)
partial = -FLT_MAX; masked = true;
} }
if (masked)
partial = -FLT_MAX;
float new_m = fmaxf(m, partial); float new_m = fmaxf(m, partial);
float alpha = __expf(m - new_m); float alpha = __expf(m - new_m);
@@ -85,7 +88,11 @@ __global__ void paged_attn_decode_split_kv_kernel(PagedAttentionParams<bf16> p)
int logical_page = pos / p.page_size; int logical_page = pos / p.page_size;
int page_offset = pos % p.page_size; int page_offset = pos % p.page_size;
int phys_page = p.page_table[batch * p.max_pages + logical_page]; int phys_page = p.page_table[batch * p.max_pages + logical_page];
if (phys_page >= 0) { if (masked) {
#pragma unroll
for (int i = 0; i < hd_per_thread; i++)
acc_reg[i] = fmaf(acc_reg[i], alpha, 0.0f);
} else if (phys_page >= 0) {
int64_t v_base = (int64_t)phys_page * p.page_size * p.kv_head * p.head_dim int64_t v_base = (int64_t)phys_page * p.page_size * p.kv_head * p.head_dim
+ (int64_t)page_offset * p.kv_head * p.head_dim + (int64_t)page_offset * p.kv_head * p.head_dim
+ (int64_t)kv_head * p.head_dim; + (int64_t)kv_head * p.head_dim;
@@ -31,6 +31,13 @@ __global__ void paged_attn_decode_split_kv_mma_kernel(PagedAttentionParams<bf16>
__shared__ __align__(16) bf16 sK[Traits::STAGES * Traits::BC * Traits::LD]; __shared__ __align__(16) bf16 sK[Traits::STAGES * Traits::BC * Traits::LD];
__shared__ __align__(16) bf16 sV[Traits::STAGES * Traits::BC * Traits::LD]; __shared__ __align__(16) bf16 sV[Traits::STAGES * Traits::BC * Traits::LD];
#pragma unroll
for (int i = lane; i < Traits::STAGES * Traits::BC * Traits::LD; i += 32) {
sK[i] = __float2bfloat16(0.0f);
sV[i] = __float2bfloat16(0.0f);
}
__syncwarp();
const int q_base = batch * p.q_stride_b + q_head0 * p.q_stride_h; const int q_base = batch * p.q_stride_b + q_head0 * p.q_stride_h;
const int qra = gid; const int qra = gid;
const int qrb = gid + 8; const int qrb = gid + 8;
@@ -68,6 +75,9 @@ __global__ void paged_attn_decode_split_kv_mma_kernel(PagedAttentionParams<bf16>
int r = i / Traits::HEAD_DIM, d = i % Traits::HEAD_DIM; int r = i / Traits::HEAD_DIM, d = i % Traits::HEAD_DIM;
int kc = kv0 + r; int kc = kv0 + r;
bool valid = (kc < p.kv_len); bool valid = (kc < p.kv_len);
if constexpr (HasMask) {
valid = valid && p.mask[batch * p.mask_b_stride + kc];
}
int phys_page = valid ? p.page_table[batch * p.max_pages + kc] : 0; int phys_page = valid ? p.page_table[batch * p.max_pages + kc] : 0;
valid = valid && (phys_page >= 0); valid = valid && (phys_page >= 0);
int page_off = kc % p.page_size; int page_off = kc % p.page_size;