Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat: adding sm_scale field for all attention APIs #145

Merged
merged 2 commits into from
Mar 1, 2024
Merged

feat: adding sm_scale field for all attention APIs #145

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
d830012
wip
yzh119 Mar 1, 2024
300c1e2
upd
yzh119 Mar 1, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
40 changes: 24 additions & 16 deletions include/flashinfer/attention/decode.cuh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@

#include <cuda/pipeline>
#include <iostream>
#include <optional>
#include <random>

#include "../cp_async.cuh"
Expand Down Expand Up @@ -816,9 +817,10 @@ cudaError_t SingleDecodeWithKVCache(DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeOut
uint32_t num_qo_heads, uint32_t num_kv_heads, uint32_t seq_len,
uint32_t head_dim, QKVLayout kv_layout = QKVLayout::kNHD,
RotaryMode rotary_mode = RotaryMode::kNone,
std::optional<float> maybe_sm_scale = std::nullopt,
float rope_scale = 1.f, float rope_theta = 1e4,
cudaStream_t stream = nullptr) {
const float sm_scale = 1.f / std::sqrt(float(head_dim));
float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));
const float rope_rcp_scale = 1.f / rope_scale;
const float rope_rcp_theta = 1.f / rope_theta;
if (num_qo_heads % num_kv_heads != 0) {
Expand Down Expand Up @@ -1134,8 +1136,7 @@ cudaError_t BatchDecodeWithPagedKVCacheDispatched(
DTypeIn* q, IdType* q_rope_position,
paged_kv_t<page_storage, kv_layout, DTypeIn, IdType> paged_kv,
kv_partition_info_t<IdType> kv_partition_info, DTypeOut* o, DTypeOut* tmp, float* lse,
float rope_scale, float rope_theta, cudaStream_t stream) {
const float sm_scale = 1.f / std::sqrt(float(HEAD_DIM));
float sm_scale, float rope_scale, float rope_theta, cudaStream_t stream) {
const float rope_rcp_scale = 1.f / rope_scale;
const float rope_rcp_theta = 1.f / rope_theta;
const uint32_t num_kv_heads = paged_kv.num_heads;
Expand Down Expand Up @@ -1229,11 +1230,13 @@ cudaError_t BatchDecodeWithPagedKVCache(
DTypeIn* q, IdType* q_rope_position,
paged_kv_t<page_storage, kv_layout, DTypeIn, IdType> paged_kv,
kv_partition_info_t<IdType> kv_partition_info, DTypeOut* o, DTypeOut* tmp, float* lse,
uint32_t num_qo_heads, RotaryMode rotary_mode = RotaryMode::kNone, float rope_scale = 1.f,
uint32_t num_qo_heads, RotaryMode rotary_mode = RotaryMode::kNone,
std::optional<float> maybe_sm_scale = std::nullopt, float rope_scale = 1.f,
float rope_theta = 1e4, cudaStream_t stream = nullptr) {
const uint32_t num_kv_heads = paged_kv.num_heads;
const uint32_t head_dim = paged_kv.head_dim;
const uint32_t batch_size = paged_kv.batch_size;
const float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));
if (num_qo_heads % num_kv_heads != 0) {
std::ostringstream err_msg;
err_msg << "num_qo_heads " << num_qo_heads << " is not a multiple of num_kv_heads "
Expand All @@ -1243,12 +1246,14 @@ cudaError_t BatchDecodeWithPagedKVCache(

DISPATCH_GQA_GROUP_SIZE(
num_qo_heads / num_kv_heads, GROUP_SIZE,
{DISPATCH_HEAD_DIM(head_dim, HEAD_DIM, {DISPATCH_ROTARY_MODE(rotary_mode, ROTARY_MODE, {
return BatchDecodeWithPagedKVCacheDispatched<
GROUP_SIZE, HEAD_DIM, page_storage, kv_layout, ROTARY_MODE, DTypeIn,
DTypeOut, IdType>(q, q_rope_position, paged_kv, kv_partition_info, o,
tmp, lse, rope_scale, rope_theta, stream);
})})});
{DISPATCH_HEAD_DIM(
head_dim, HEAD_DIM, {DISPATCH_ROTARY_MODE(rotary_mode, ROTARY_MODE, {
return BatchDecodeWithPagedKVCacheDispatched<GROUP_SIZE, HEAD_DIM, page_storage,
kv_layout, ROTARY_MODE, DTypeIn, DTypeOut,
IdType>(
q, q_rope_position, paged_kv, kv_partition_info, o, tmp, lse, sm_scale, rope_scale,
rope_theta, stream);
})})});

return cudaSuccess;
}
Expand All @@ -1258,9 +1263,8 @@ template <uint32_t GROUP_SIZE, uint32_t HEAD_DIM, QKVLayout KV_LAYOUT, RotaryMod
cudaError_t BatchDecodeWithPaddedKVCacheDispatched(DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeIn* o,
DTypeOut* tmp, float* lse, uint32_t batch_size,
uint32_t padded_kv_len, uint32_t num_qo_heads,
float rope_scale, float rope_theta,
cudaStream_t stream) {
const float sm_scale = 1.f / std::sqrt(float(HEAD_DIM));
float sm_scale, float rope_scale,
float rope_theta, cudaStream_t stream) {
const float rope_rcp_scale = 1.f / rope_scale;
const float rope_rcp_theta = 1.f / rope_theta;
const uint32_t num_kv_heads = num_qo_heads / GROUP_SIZE;
Expand Down Expand Up @@ -1301,7 +1305,11 @@ cudaError_t BatchDecodeWithPaddedKVCache(
DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeIn* o, DTypeOut* tmp, float* lse, uint32_t batch_size,
uint32_t padded_kv_len, uint32_t num_qo_heads, uint32_t num_kv_heads, uint32_t head_dim,
QKVLayout kv_layout = QKVLayout::kNHD, RotaryMode rotary_mode = RotaryMode::kNone,
float rope_scale = 1.f, float rope_theta = 1e4, cudaStream_t stream = nullptr) {
std::optional<float> sm_scale = std::nullopt, float rope_scale = 1.f, float rope_theta = 1e4,
cudaStream_t stream = nullptr) {
if (!sm_scale.has_value()) {
sm_scale = 1.f / std::sqrt(float(head_dim));
}
if (num_qo_heads % num_kv_heads != 0) {
std::ostringstream err_msg;
err_msg << "num_qo_heads " << num_qo_heads << " is not a multiple of num_kv_heads "
Expand All @@ -1317,8 +1325,8 @@ cudaError_t BatchDecodeWithPaddedKVCache(
rotary_mode, ROTARY_MODE, {DISPATCH_LAYOUT(kv_layout, KV_LAYOUT, {
return BatchDecodeWithPaddedKVCacheDispatched<GROUP_SIZE, HEAD_DIM, KV_LAYOUT,
ROTARY_MODE, DTypeIn, DTypeOut>(
q, k, v, o, tmp, lse, batch_size, padded_kv_len, num_qo_heads, rope_scale,
rope_theta, stream);
q, k, v, o, tmp, lse, batch_size, padded_kv_len, num_qo_heads, sm_scale,
rope_scale, rope_theta, stream);
})})})});
return cudaSuccess;
}
Expand Down
62 changes: 34 additions & 28 deletions include/flashinfer/attention/prefill.cuh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
#endif
#include <cuda_runtime.h>

#include <optional>
#include <tuple>

#include "../cp_async.cuh"
Expand Down Expand Up @@ -1563,9 +1564,9 @@ template <uint32_t GROUP_SIZE, uint32_t HEAD_DIM, QKVLayout KV_LAYOUT, RotaryMod
bool ALLOW_FP16_QK_REDUCTION, bool CAUSAL, typename DTypeIn, typename DTypeOut>
cudaError_t SinglePrefillWithKVCacheDispatched(DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeOut* o,
float* tmp, float* lse, uint32_t num_kv_heads,
uint32_t qo_len, uint32_t kv_len, float rope_scale,
float rope_theta, cudaStream_t stream) {
const float sm_scale = 1.f / std::sqrt(float(HEAD_DIM));
uint32_t qo_len, uint32_t kv_len, float sm_scale,
float rope_scale, float rope_theta,
cudaStream_t stream) {
const float log2_rope_rcp_scale = -std::log2f(rope_scale);
const float log2_rope_rcp_theta = -std::log2f(rope_theta);
if (kv_len < qo_len && CAUSAL) {
Expand Down Expand Up @@ -1714,14 +1715,14 @@ cudaError_t SinglePrefillWithKVCacheDispatched(DTypeIn* q, DTypeIn* k, DTypeIn*
* \return status Indicates whether CUDA calls are successful
*/
template <typename DTypeIn, typename DTypeOut>
cudaError_t SinglePrefillWithKVCache(DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeOut* o, float* tmp,
float* lse, uint32_t num_qo_heads, uint32_t num_kv_heads,
uint32_t qo_len, uint32_t kv_len, uint32_t head_dim,
bool causal = true, QKVLayout kv_layout = QKVLayout::kNHD,
RotaryMode rotary_mode = RotaryMode::kNone,
bool allow_fp16_qk_reduction = false, float rope_scale = 1.f,
float rope_theta = 1e4, cudaStream_t stream = nullptr) {
cudaError_t SinglePrefillWithKVCache(
DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeOut* o, float* tmp, float* lse, uint32_t num_qo_heads,
uint32_t num_kv_heads, uint32_t qo_len, uint32_t kv_len, uint32_t head_dim, bool causal = true,
QKVLayout kv_layout = QKVLayout::kNHD, RotaryMode rotary_mode = RotaryMode::kNone,
bool allow_fp16_qk_reduction = false, std::optional<float> maybe_sm_scale = std::nullopt,
float rope_scale = 1.f, float rope_theta = 1e4, cudaStream_t stream = nullptr) {
const uint32_t group_size = num_qo_heads / num_kv_heads;
const float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));
DISPATCH_ALLOW_FP16_QK_REDUCTION(
allow_fp16_qk_reduction, ALLOW_FP16_QK_REDUCTION,
{DISPATCH_GQA_GROUP_SIZE(
Expand All @@ -1734,9 +1735,9 @@ cudaError_t SinglePrefillWithKVCache(DTypeIn* q, DTypeIn* k, DTypeIn* v, DTypeOu
rotary_mode, ROTARY_MODE, {DISPATCH_LAYOUT(kv_layout, KV_LAYOUT, {
SinglePrefillWithKVCacheDispatched<GROUP_SIZE, HEAD_DIM, KV_LAYOUT,
ROTARY_MODE, ALLOW_FP16_QK_REDUCTION,
CAUSAL>(q, k, v, o, tmp, lse,
num_kv_heads, qo_len, kv_len,
rope_scale, rope_theta, stream);
CAUSAL>(
q, k, v, o, tmp, lse, num_kv_heads, qo_len, kv_len, sm_scale,
rope_scale, rope_theta, stream);
})})})})})});
return cudaSuccess;
}
Expand All @@ -1748,9 +1749,8 @@ cudaError_t BatchPrefillWithRaggedKVCacheDispatched(
DTypeIn* q, IdType* request_indices, IdType* tile_indices, IdType* qo_indptr, DTypeIn* k,
DTypeIn* v, IdType* kv_indptr, IdType* q_rope_position, IdType* k_rope_pos_offset, DTypeOut* o,
float* tmp, float* lse, const uint32_t batch_size, const uint32_t num_qo_tiles,
const uint32_t num_kv_heads, const float rope_scale, const float rope_theta,
cudaStream_t stream = nullptr) {
const float sm_scale = 1.f / std::sqrt(float(HEAD_DIM));
const uint32_t num_kv_heads, const float sm_scale, const float rope_scale,
const float rope_theta, cudaStream_t stream = nullptr) {
const float log2_rope_rcp_scale = -std::log2f(rope_scale);
const float log2_rope_rcp_theta = -std::log2f(rope_theta);
constexpr uint32_t num_warps = 4;
Expand Down Expand Up @@ -1826,8 +1826,10 @@ cudaError_t BatchPrefillWithRaggedKVCache(
const uint32_t batch_size, const uint32_t num_qo_heads, const uint32_t num_kv_heads,
const uint32_t head_dim, bool causal = true, QKVLayout kv_layout = QKVLayout::kNHD,
RotaryMode rotary_mode = RotaryMode::kNone, bool allow_fp16_qk_reduction = false,
const float rope_scale = 1.f, const float rope_theta = 1e4, cudaStream_t stream = nullptr) {
std::optional<float> maybe_sm_scale = std::nullopt, const float rope_scale = 1.f,
const float rope_theta = 1e4, cudaStream_t stream = nullptr) {
const uint32_t group_size = num_qo_heads / num_kv_heads;
const float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));

uint32_t num_frags_x, num_qo_tiles;
std::vector<IdType> request_indices_h, tile_indices_h;
Expand Down Expand Up @@ -1865,7 +1867,8 @@ cudaError_t BatchPrefillWithRaggedKVCache(
ALLOW_FP16_QK_REDUCTION, CAUSAL, DTypeIn, DTypeOut, IdType>(
q, request_indices_d, tile_indices_d, qo_indptr, k, v, kv_indptr,
q_rope_position, k_rope_pos_offset, o, tmp, lse, batch_size,
num_qo_tiles, num_kv_heads, rope_scale, rope_theta, stream);
num_qo_tiles, num_kv_heads, sm_scale, rope_scale, rope_theta,
stream);
})})})})})})});

FLASHINFER_CUDA_CALL(cudaFreeAsync(request_indices_d, stream));
Expand Down Expand Up @@ -1901,12 +1904,14 @@ template <PageStorage page_storage, QKVLayout kv_layout, uint32_t num_frags_x, u
cudaError_t BatchPrefillWithPagedKVCacheFallbackDispatched(
DTypeIn* q, IdType* request_indices, IdType* tile_indices, IdType* qo_indptr,
IdType* q_rope_position, paged_kv_t<page_storage, kv_layout, DTypeIn, IdType> paged_kv,
DTypeOut* o, float* tmp, float* lse, uint32_t num_qo_tiles, float rope_scale = 1.f,
DTypeOut* o, float* tmp, float* lse, uint32_t num_qo_tiles,
std::optional<float> maybe_sm_scale = std::nullopt, float rope_scale = 1.f,
float rope_theta = 1e4, cudaStream_t stream = nullptr) {
constexpr QKVLayout KV_LAYOUT = QKVLayout::kNHD;
const uint32_t num_kv_heads = paged_kv.num_heads;
const uint32_t head_dim = paged_kv.head_dim;
const uint32_t batch_size = paged_kv.batch_size;
const float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));

std::vector<IdType> kv_indptr_h(paged_kv.batch_size + 1);

Expand All @@ -1929,8 +1934,8 @@ cudaError_t BatchPrefillWithPagedKVCacheFallbackDispatched(
ALLOW_FP16_QK_REDUCTION, CAUSAL, DTypeIn, DTypeOut,
IdType>(
q, request_indices, tile_indices, qo_indptr, keys, values, kv_indptr, q_rope_position,
paged_kv.rope_pos_offset, o, tmp, lse, batch_size, num_qo_tiles, num_kv_heads, rope_scale,
rope_theta, stream);
paged_kv.rope_pos_offset, o, tmp, lse, batch_size, num_qo_tiles, num_kv_heads, sm_scale,
rope_scale, rope_theta, stream);

FLASHINFER_CUDA_CALL(cudaFreeAsync(keys, stream));
FLASHINFER_CUDA_CALL(cudaFreeAsync(values, stream));
Expand All @@ -1946,9 +1951,8 @@ template <PageStorage page_storage, QKVLayout kv_layout, uint32_t num_frags_x, u
cudaError_t BatchPrefillWithPagedKVCacheDispatched(
DTypeIn* q, IdType* request_indices, IdType* tile_indices, IdType* qo_indptr,
IdType* q_rope_position, paged_kv_t<page_storage, kv_layout, DTypeIn, IdType> paged_kv,
DTypeOut* o, float* tmp, float* lse, uint32_t num_qo_tiles, float rope_scale, float rope_theta,
cudaStream_t stream) {
const float sm_scale = 1.f / std::sqrt(float(paged_kv.head_dim));
DTypeOut* o, float* tmp, float* lse, uint32_t num_qo_tiles, float sm_scale, float rope_scale,
float rope_theta, cudaStream_t stream) {
const float log2_rope_rcp_scale = -std::log2f(rope_scale);
const float log2_rope_rcp_theta = -std::log2f(rope_theta);
constexpr uint32_t num_warps = 4;
Expand Down Expand Up @@ -2022,11 +2026,13 @@ cudaError_t BatchPrefillWithPagedKVCache(
paged_kv_t<page_storage, kv_layout, DTypeIn, IdType> paged_kv, DTypeOut* o, float* tmp,
float* lse, uint32_t num_qo_heads, bool causal = true,
RotaryMode rotary_mode = RotaryMode::kNone, bool allow_fp16_qk_reduction = false,
float rope_scale = 1.f, float rope_theta = 1e4, cudaStream_t stream = nullptr) {
std::optional<float> maybe_sm_scale = std::nullopt, float rope_scale = 1.f,
float rope_theta = 1e4, cudaStream_t stream = nullptr) {
const uint32_t num_kv_heads = paged_kv.num_heads;
const uint32_t head_dim = paged_kv.head_dim;
const uint32_t batch_size = paged_kv.batch_size;
const uint32_t group_size = num_qo_heads / num_kv_heads;
const float sm_scale = maybe_sm_scale.value_or(1.f / std::sqrt(float(head_dim)));

uint32_t num_frags_x, num_qo_tiles;
std::vector<IdType> request_indices_h, tile_indices_h;
Expand Down Expand Up @@ -2068,16 +2074,16 @@ cudaError_t BatchPrefillWithPagedKVCache(
ROTARY_MODE, ALLOW_FP16_QK_REDUCTION, CAUSAL, DTypeIn,
DTypeOut, IdType>(q, request_indices_d, tile_indices_d,
qo_indptr, q_rope_position, paged_kv, o,
tmp, lse, num_qo_tiles, rope_scale,
rope_theta, stream);
tmp, lse, num_qo_tiles, sm_scale,
rope_scale, rope_theta, stream);
} else {
return BatchPrefillWithPagedKVCacheDispatched<
page_storage, kv_layout, NUM_FRAGS_X, PAGE_SIZE, GROUP_SIZE,
HEAD_DIM, ROTARY_MODE, ALLOW_FP16_QK_REDUCTION, CAUSAL,
DTypeIn, DTypeOut, IdType>(
q, request_indices_d, tile_indices_d, qo_indptr,
q_rope_position, paged_kv, o, tmp, lse, num_qo_tiles,
rope_scale, rope_theta, stream);
sm_scale, rope_scale, rope_theta, stream);
}
})

Expand Down
Loading