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Commit 5a683756 authored by Po Yen, Chen's avatar Po Yen, Chen
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Re-format kernel

parent b618806b
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Showing with 1030 additions and 910 deletions
example/ck_tile/18_paged_attention/include/kernel/paged_attention_kernel.hpp
View file @ 5a683756
......@@ -24,41 +24,42 @@
#include "attention/dtype_fp8.cuh"
#include "quantization/fp8/amd/quant_utils.cuh"
#if defined(__HIPCC__) && (defined(__gfx90a__) || defined(__gfx940__) || \
defined(__gfx941__) || defined(__gfx942__))
#define __HIP__MI300_MI250__
#if defined(__HIPCC__) && \
(defined(__gfx90a__) || defined(__gfx940__) || defined(__gfx941__) || defined(__gfx942__))
#define __HIP__MI300_MI250__
#endif
#if defined(NDEBUG)
#undef NDEBUG
#include <assert.h>
#define UNREACHABLE_CODE assert(false);
#define NDEBUG
#undef NDEBUG
#include <assert.h>
#define UNREACHABLE_CODE assert(false);
#define NDEBUG
#else
#define UNREACHABLE_CODE assert(false);
#define UNREACHABLE_CODE assert(false);
#endif
#define MAX(a, b) ((a) > (b) ? (a) : (b))
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define DIVIDE_ROUND_UP(a, b) (((a) + (b) - 1) / (b))
#define DIVIDE_ROUND_UP(a, b) (((a) + (b)-1) / (b))
#if defined(__HIP__MI300_MI250__) // TODO: Add NAVI support
#define GCN_MFMA_INSTR1 __builtin_amdgcn_mfma_f32_16x16x4f32
#define GCN_MFMA_INSTR __builtin_amdgcn_mfma_f32_4x4x4f16
#define GCN_MFMA_INSTR1 __builtin_amdgcn_mfma_f32_16x16x4f32
#define GCN_MFMA_INSTR __builtin_amdgcn_mfma_f32_4x4x4f16
using floatx4 = __attribute__((__vector_size__(4 * sizeof(float)))) float;
using float16x4 =
__attribute__((__vector_size__(4 * sizeof(_Float16)))) _Float16;
using float16x4 = __attribute__((__vector_size__(4 * sizeof(_Float16)))) _Float16;
typedef float16x4 _Half4;
typedef struct _Half8 {
typedef struct _Half8
{
_Half4 xy[2];
} _Half8;
using bit16_t = uint16_t;
using bit16x4 = __attribute__((__vector_size__(4 * sizeof(uint16_t)))) uint16_t;
typedef bit16x4 _B16x4;
typedef struct _B16x8 {
typedef struct _B16x8
{
_B16x4 xy[2];
} _B16x8;
......@@ -68,144 +69,191 @@ using bit8_t = uint8_t;
////// Non temporal load stores ///////
template <typename T>
__device__ __forceinline__ T load(T* addr) {
__device__ __forceinline__ T load(T* addr)
{
return addr[0];
}
template <typename T>
__device__ __forceinline__ void store(T value, T* addr) {
__device__ __forceinline__ void store(T value, T* addr)
{
addr[0] = value;
}
template <typename T, int absz, int cbid, int blgp>
__device__ __forceinline__ floatx4 gcn_mfma_instr(const _B16x4& inpA,
const _B16x4& inpB,
const floatx4& inpC) {
if constexpr (std::is_same<T, _Float16>::value) {
return __builtin_amdgcn_mfma_f32_4x4x4f16(inpA, inpB, inpC, absz, cbid,
blgp);
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
return __builtin_amdgcn_mfma_f32_4x4x4bf16_1k(inpA, inpB, inpC, absz, cbid,
blgp);
} else {
const floatx4& inpC)
{
if constexpr(std::is_same<T, _Float16>::value)
{
return __builtin_amdgcn_mfma_f32_4x4x4f16(inpA, inpB, inpC, absz, cbid, blgp);
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
return __builtin_amdgcn_mfma_f32_4x4x4bf16_1k(inpA, inpB, inpC, absz, cbid, blgp);
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T>
__device__ __forceinline__ float to_float(const T& inp) {
if constexpr (std::is_same<T, _Float16>::value) {
__device__ __forceinline__ float to_float(const T& inp)
{
if constexpr(std::is_same<T, _Float16>::value)
{
return (float)inp;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
return __bfloat162float(inp);
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T>
__device__ __forceinline__ float to_float_b16(const bit16_t& inp) {
union tmpcvt {
__device__ __forceinline__ float to_float_b16(const bit16_t& inp)
{
union tmpcvt
{
bit16_t u;
_Float16 f;
__hip_bfloat16 b;
} t16;
t16.u = inp;
if constexpr (std::is_same<T, _Float16>::value) {
if constexpr(std::is_same<T, _Float16>::value)
{
return (float)t16.f;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
return __bfloat162float(t16.b);
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T>
__device__ __forceinline__ T from_float(const float& inp) {
if constexpr (std::is_same<T, _Float16>::value) {
__device__ __forceinline__ T from_float(const float& inp)
{
if constexpr(std::is_same<T, _Float16>::value)
{
return (_Float16)inp;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
return __float2bfloat16(inp);
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T>
__device__ __forceinline__ _B16x4 from_floatx4(const floatx4& inp) {
union tmpcvt {
__device__ __forceinline__ _B16x4 from_floatx4(const floatx4& inp)
{
union tmpcvt
{
uint16_t u;
_Float16 f;
__hip_bfloat16 b;
} t16;
_B16x4 ret;
if constexpr (std::is_same<T, _Float16>::value) {
#pragma unroll
for (int i = 0; i < 4; i++) {
if constexpr(std::is_same<T, _Float16>::value)
{
#pragma unroll
for(int i = 0; i < 4; i++)
{
t16.f = (_Float16)inp[i];
ret[i] = t16.u;
}
return ret;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
#pragma unroll
for (int i = 0; i < 4; i++) {
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
#pragma unroll
for(int i = 0; i < 4; i++)
{
t16.b = __float2bfloat16(inp[i]);
ret[i] = t16.u;
}
return ret;
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T>
__device__ __forceinline__ _B16x4 addx4(const _B16x4& inp1,
const _B16x4& inp2) {
union tmpcvt {
__device__ __forceinline__ _B16x4 addx4(const _B16x4& inp1, const _B16x4& inp2)
{
union tmpcvt
{
uint16_t u;
_Float16 f;
__hip_bfloat16 b;
} t1, t2, res;
_B16x4 ret;
if constexpr (std::is_same<T, _Float16>::value) {
#pragma unroll
for (int i = 0; i < 4; i++) {
if constexpr(std::is_same<T, _Float16>::value)
{
#pragma unroll
for(int i = 0; i < 4; i++)
{
t1.u = inp1[i];
t2.u = inp2[i];
res.f = t1.f + t2.f;
ret[i] = res.u;
}
return ret;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
#pragma unroll
for (int i = 0; i < 4; i++) {
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
#pragma unroll
for(int i = 0; i < 4; i++)
{
t1.u = inp1[i];
t2.u = inp2[i];
res.b = t1.b + t2.b;
ret[i] = res.u;
}
return ret;
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
template <typename T, vllm::Fp8KVCacheDataType KV_DTYPE>
__device__ __forceinline__ _B16x8 scaled_convert_b8x8(const _B8x8 input,
const float scale) {
union alignas(16) {
__device__ __forceinline__ _B16x8 scaled_convert_b8x8(const _B8x8 input, const float scale)
{
union alignas(16)
{
uint4 u4;
_B16x8 u16x8;
vllm::bf16_8_t b16x8;
} tmp;
if constexpr (std::is_same<T, _Float16>::value) {
if constexpr(std::is_same<T, _Float16>::value)
{
tmp.u4 = vllm::fp8::scaled_convert<uint4, _B8x8, KV_DTYPE>(input, scale);
return tmp.u16x8;
} else if constexpr (std::is_same<T, __hip_bfloat16>::value) {
tmp.b16x8 = vllm::fp8::scaled_convert<vllm::bf16_8_t, _B8x8, KV_DTYPE>(
input, scale);
}
else if constexpr(std::is_same<T, __hip_bfloat16>::value)
{
tmp.b16x8 = vllm::fp8::scaled_convert<vllm::bf16_8_t, _B8x8, KV_DTYPE>(input, scale);
return tmp.u16x8;
} else {
}
else
{
static_assert(false, "unsupported 16b dtype");
}
}
......@@ -214,9 +262,13 @@ __device__ __forceinline__ _B16x8 scaled_convert_b8x8(const _B8x8 input,
// grid (num_seqs, num_partitions,num_heads/gqa_ratio)
// block (partition size)
template <typename scalar_t, typename cache_t,
vllm::Fp8KVCacheDataType KV_DTYPE, typename OUTT, int BLOCK_SIZE,
int HEAD_SIZE, int NUM_THREADS,
template <typename scalar_t,
typename cache_t,
vllm::Fp8KVCacheDataType KV_DTYPE,
typename OUTT,
int BLOCK_SIZE,
int HEAD_SIZE,
int NUM_THREADS,
int GQA_RATIO>
__global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const scalar_t* __restrict__ q, // [num_seqs, num_heads, head_size]
......@@ -224,20 +276,26 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
// head_size/x, block_size, x]
const cache_t* __restrict__ v_cache, // [num_blocks, num_kv_heads,
// head_size, block_size]
const int num_kv_heads, const float scale,
const int num_kv_heads,
const float scale,
const int* __restrict__ block_tables, // [num_seqs, max_num_blocks_per_seq]
const int* __restrict__ context_lens, // [num_seqs]
const int max_num_blocks_per_seq,
const float* __restrict__ alibi_slopes, // [num_heads]
const int q_stride, const int kv_block_stride, const int kv_head_stride,
const int q_stride,
const int kv_block_stride,
const int kv_head_stride,
float* __restrict__ exp_sums, // [num_seqs, num_heads, max_num_partitions]
float* __restrict__ max_logits, // [num_seqs, num_heads,
// max_num_partitions]
scalar_t* __restrict__ out, // [num_seqs, num_heads, max_num_partitions,
// head_size]
OUTT* __restrict__ final_out, // [num_seqs, num_heads, head_size]
int max_ctx_blocks, float k_scale, float v_scale,
const float* __restrict__ fp8_out_scale_ptr) {
int max_ctx_blocks,
float k_scale,
float v_scale,
const float* __restrict__ fp8_out_scale_ptr)
{
constexpr int NWARPS = NUM_THREADS / WARP_SIZE;
const int warpid = threadIdx.x / WARP_SIZE;
const int laneid = threadIdx.x % WARP_SIZE;
......@@ -251,11 +309,11 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const int context_len = context_lens[seq_idx];
const int partition_start_token_idx = partition_idx * partition_size;
// exit if partition is out of context for seq
if (partition_start_token_idx >= context_len) {
if(partition_start_token_idx >= context_len)
{
return;
}
constexpr int QHLOOP =
DIVIDE_ROUND_UP(GQA_RATIO, 4); // each 4 lanes fetch 4 different qheads,
constexpr int QHLOOP = DIVIDE_ROUND_UP(GQA_RATIO, 4); // each 4 lanes fetch 4 different qheads,
// total qheads =8, so qhloop is 2
constexpr int GQA_RATIO4 = 4 * QHLOOP;
__shared__ float shared_qk_max[NWARPS][GQA_RATIO4 + 1];
......@@ -266,16 +324,16 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
_B16x8 Klocal[KHELOOP];
_B8x8 Klocalb8[KHELOOP];
constexpr int VHELOOP =
HEAD_SIZE /
WARP_SIZE; // v head_size dimension is distributed across lanes
HEAD_SIZE / WARP_SIZE; // v head_size dimension is distributed across lanes
constexpr int VTLOOP = 8; // 16 separate 4xtokens across warp -> 16/2
// 8xtokens
_B16x8 Vlocal[VHELOOP][VTLOOP];
_B8x8 Vlocalb8[VHELOOP][VTLOOP];
floatx4 dout[QHLOOP];
float qk_max[QHLOOP];
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
dout[h] = {0};
qk_max[h] = -FLT_MAX;
}
......@@ -283,16 +341,19 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const int wg_start_head_idx = blockIdx.z * GQA_RATIO;
const int wg_start_kv_head_idx = blockIdx.z;
const int warp_start_token_idx =
partition_start_token_idx + warpid * WARP_SIZE;
const int warp_start_token_idx = partition_start_token_idx + warpid * WARP_SIZE;
if (warp_start_token_idx >= context_len) { // warp out of context
#pragma unroll
for (int h = 0; h < GQA_RATIO4; h++) {
if(warp_start_token_idx >= context_len)
{ // warp out of context
#pragma unroll
for(int h = 0; h < GQA_RATIO4; h++)
{
shared_qk_max[warpid][h] = -FLT_MAX;
shared_exp_sum[warpid][h] = 0.0f;
}
} else { // warp within context
}
else
{ // warp within context
const int num_context_blocks = DIVIDE_ROUND_UP(context_len, BLOCK_SIZE);
const int last_ctx_block = num_context_blocks - 1;
......@@ -302,23 +363,23 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const int local_token_idx = threadIdx.x;
const int global_token_idx = partition_start_token_idx + local_token_idx;
const int block_idx = (global_token_idx < context_len)
? global_token_idx / BLOCK_SIZE
: last_ctx_block;
const int block_idx =
(global_token_idx < context_len) ? global_token_idx / BLOCK_SIZE : last_ctx_block;
// fetch block number for q and k
// int32 physical_block_number leads to overflow when multiplied with
// kv_block_stride
const int64_t physical_block_number =
static_cast<int64_t>(block_table[block_idx]);
const int64_t physical_block_number = static_cast<int64_t>(block_table[block_idx]);
// fetch vphysical block numbers up front
constexpr int VBLOCKS = 8 * VTLOOP / BLOCK_SIZE;
int vphysical_blocks[VBLOCKS];
const int warp_start_block_idx = warp_start_token_idx / BLOCK_SIZE;
if constexpr (GQA_RATIO < 12) {
#pragma unroll
for (int b = 0; b < VBLOCKS; b++) {
if constexpr(GQA_RATIO < 12)
{
#pragma unroll
for(int b = 0; b < VBLOCKS; b++)
{
const int vblock_idx = warp_start_block_idx + b;
const int vblock_idx_ctx =
(vblock_idx <= last_ctx_block) ? vblock_idx : last_ctx_block;
......@@ -327,20 +388,22 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
// each 4 lanes fetch 8 helems, so warp fetches 8*16 = 128 helems
const scalar_t* q_ptr =
q + seq_idx * q_stride + wg_start_head_idx * HEAD_SIZE;
const scalar_t* q_ptr = q + seq_idx * q_stride + wg_start_head_idx * HEAD_SIZE;
const _B16x8* q_ptrh8 = reinterpret_cast<const _B16x8*>(q_ptr);
const int qhead_elemh8 = laneid / 4;
#pragma unroll
for (int h = 0; h < QHLOOP - 1; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP - 1; h++)
{
const int qhead_idx = h * 4 + lane4id;
Qlocal[h] = q_ptrh8[qhead_idx * HEAD_SIZE / 8 + qhead_elemh8];
}
const int final_qhead_idx = 4 * (QHLOOP - 1) + lane4id;
if (final_qhead_idx < GQA_RATIO) {
Qlocal[QHLOOP - 1] =
q_ptrh8[final_qhead_idx * HEAD_SIZE / 8 + qhead_elemh8];
} else {
if(final_qhead_idx < GQA_RATIO)
{
Qlocal[QHLOOP - 1] = q_ptrh8[final_qhead_idx * HEAD_SIZE / 8 + qhead_elemh8];
}
else
{
Qlocal[QHLOOP - 1].xy[0] = {0};
Qlocal[QHLOOP - 1].xy[1] = {0};
}
......@@ -351,17 +414,22 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const int physical_block_offset =
local_token_idx % BLOCK_SIZE; // since x=half8, physical_block_offset
// is already cast as _H8
if constexpr (KV_DTYPE == vllm::Fp8KVCacheDataType::kAuto) {
if constexpr(KV_DTYPE == vllm::Fp8KVCacheDataType::kAuto)
{
const _B16x8* k_ptrh8 = reinterpret_cast<const _B16x8*>(k_ptr);
#pragma unroll
for (int d = 0; d < KHELOOP; d++) {
#pragma unroll
for(int d = 0; d < KHELOOP; d++)
{
Klocal[d] = k_ptrh8[d * BLOCK_SIZE + physical_block_offset];
}
} else {
}
else
{
constexpr int X = 16 / sizeof(cache_t);
const cache_t* k_ptr2 = k_ptr + physical_block_offset * X;
#pragma unroll
for (int d = 0; d < KHELOOP; d++) {
#pragma unroll
for(int d = 0; d < KHELOOP; d++)
{
const int head_elem = d * 8;
const int offset1 = head_elem / X;
const int offset2 = head_elem % X;
......@@ -371,20 +439,23 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
float alibi_slope[QHLOOP];
if (alibi_slopes != nullptr) {
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
if(alibi_slopes != nullptr)
{
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
const int qhead_idx = h * 4 + lane4id;
alibi_slope[h] = (qhead_idx < GQA_RATIO)
? alibi_slopes[wg_start_head_idx + qhead_idx]
: 0.f;
alibi_slope[h] =
(qhead_idx < GQA_RATIO) ? alibi_slopes[wg_start_head_idx + qhead_idx] : 0.f;
}
}
// fetch vphysical block numbers up front
if constexpr (GQA_RATIO >= 12) {
#pragma unroll
for (int b = 0; b < VBLOCKS; b++) {
if constexpr(GQA_RATIO >= 12)
{
#pragma unroll
for(int b = 0; b < VBLOCKS; b++)
{
const int vblock_idx = warp_start_block_idx + b;
const int vblock_idx_ctx =
(vblock_idx <= last_ctx_block) ? vblock_idx : last_ctx_block;
......@@ -393,48 +464,53 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
const cache_t* v_ptr = v_cache + wg_start_kv_head_idx * kv_head_stride;
if constexpr (KV_DTYPE == vllm::Fp8KVCacheDataType::kAuto) {
if constexpr(KV_DTYPE == vllm::Fp8KVCacheDataType::kAuto)
{
const _B16x8* v_ptrh8 = reinterpret_cast<const _B16x8*>(v_ptr);
// iterate over each v block
#pragma unroll
for (int b = 0; b < VBLOCKS; b++) {
#pragma unroll
for(int b = 0; b < VBLOCKS; b++)
{
// int32 physical_block_number leads to overflow when multiplied with
// kv_block_stride
const int64_t vphysical_block_number =
static_cast<int64_t>(vphysical_blocks[b]);
const _B16x8* v_ptrh8b =
v_ptrh8 + (vphysical_block_number * kv_block_stride) / 8;
const int64_t vphysical_block_number = static_cast<int64_t>(vphysical_blocks[b]);
const _B16x8* v_ptrh8b = v_ptrh8 + (vphysical_block_number * kv_block_stride) / 8;
// iterate over each head elem (within head_size)
#pragma unroll
for (int h = 0; h < VHELOOP; h++) {
#pragma unroll
for(int h = 0; h < VHELOOP; h++)
{
const int head_size_elem = h * WARP_SIZE + laneid;
const _B16x8* v_ptrh8be = v_ptrh8b + head_size_elem * BLOCK_SIZE / 8;
// iterate over all velems within block
#pragma unroll
for (int d = 0; d < BLOCK_SIZE / 8; d++) {
#pragma unroll
for(int d = 0; d < BLOCK_SIZE / 8; d++)
{
Vlocal[h][b * BLOCK_SIZE / 8 + d] = v_ptrh8be[d];
}
}
}
} else {
}
else
{
const _B8x8* v_ptrh8 = reinterpret_cast<const _B8x8*>(v_ptr);
// iterate over each v block
#pragma unroll
for (int b = 0; b < VBLOCKS; b++) {
#pragma unroll
for(int b = 0; b < VBLOCKS; b++)
{
// int32 physical_block_number leads to overflow when multiplied with
// kv_block_stride
const int64_t vphysical_block_number =
static_cast<int64_t>(vphysical_blocks[b]);
const _B8x8* v_ptrh8b =
v_ptrh8 + (vphysical_block_number * kv_block_stride) / 8;
const int64_t vphysical_block_number = static_cast<int64_t>(vphysical_blocks[b]);
const _B8x8* v_ptrh8b = v_ptrh8 + (vphysical_block_number * kv_block_stride) / 8;
// iterate over each head elem (within head_size)
#pragma unroll
for (int h = 0; h < VHELOOP; h++) {
#pragma unroll
for(int h = 0; h < VHELOOP; h++)
{
const int head_size_elem = h * WARP_SIZE + laneid;
const _B8x8* v_ptrh8be = v_ptrh8b + head_size_elem * BLOCK_SIZE / 8;
// iterate over all velems within block
#pragma unroll
for (int d = 0; d < BLOCK_SIZE / 8; d++) {
#pragma unroll
for(int d = 0; d < BLOCK_SIZE / 8; d++)
{
// Vlocalb8[h][b * BLOCK_SIZE / 8 + d] = v_ptrh8be[d];
const _B8x8 Vlocalb8 = v_ptrh8be[d];
Vlocal[h][b * BLOCK_SIZE / 8 + d] =
......@@ -444,91 +520,80 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
}
if constexpr (KV_DTYPE != vllm::Fp8KVCacheDataType::kAuto) {
#pragma unroll
for (int d = 0; d < KHELOOP; d++) {
Klocal[d] =
scaled_convert_b8x8<scalar_t, KV_DTYPE>(Klocalb8[d], k_scale);
}
}
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
dout[h] = gcn_mfma_instr<scalar_t, 4, 0, 0>(Qlocal[h].xy[0],
Klocal[0].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 0, 0>(Qlocal[h].xy[1],
Klocal[0].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 1, 0>(Qlocal[h].xy[0],
Klocal[1].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 1, 0>(Qlocal[h].xy[1],
Klocal[1].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 2, 0>(Qlocal[h].xy[0],
Klocal[2].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 2, 0>(Qlocal[h].xy[1],
Klocal[2].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 3, 0>(Qlocal[h].xy[0],
Klocal[3].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 3, 0>(Qlocal[h].xy[1],
Klocal[3].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 4, 0>(Qlocal[h].xy[0],
Klocal[4].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 4, 0>(Qlocal[h].xy[1],
Klocal[4].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 5, 0>(Qlocal[h].xy[0],
Klocal[5].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 5, 0>(Qlocal[h].xy[1],
Klocal[5].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 6, 0>(Qlocal[h].xy[0],
Klocal[6].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 6, 0>(Qlocal[h].xy[1],
Klocal[6].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 7, 0>(Qlocal[h].xy[0],
Klocal[7].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 7, 0>(Qlocal[h].xy[1],
Klocal[7].xy[1], dout[h]);
if constexpr (KHELOOP > 8) {
dout[h] = gcn_mfma_instr<scalar_t, 4, 8, 0>(Qlocal[h].xy[0],
Klocal[8].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 8, 0>(Qlocal[h].xy[1],
Klocal[8].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 9, 0>(Qlocal[h].xy[0],
Klocal[9].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 9, 0>(Qlocal[h].xy[1],
Klocal[9].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 10, 0>(Qlocal[h].xy[0],
Klocal[10].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 10, 0>(Qlocal[h].xy[1],
Klocal[10].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 11, 0>(Qlocal[h].xy[0],
Klocal[11].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 11, 0>(Qlocal[h].xy[1],
Klocal[11].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 12, 0>(Qlocal[h].xy[0],
Klocal[12].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 12, 0>(Qlocal[h].xy[1],
Klocal[12].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 13, 0>(Qlocal[h].xy[0],
Klocal[13].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 13, 0>(Qlocal[h].xy[1],
Klocal[13].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 14, 0>(Qlocal[h].xy[0],
Klocal[14].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 14, 0>(Qlocal[h].xy[1],
Klocal[14].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 15, 0>(Qlocal[h].xy[0],
Klocal[15].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 15, 0>(Qlocal[h].xy[1],
Klocal[15].xy[1], dout[h]);
if constexpr(KV_DTYPE != vllm::Fp8KVCacheDataType::kAuto)
{
#pragma unroll
for(int d = 0; d < KHELOOP; d++)
{
Klocal[d] = scaled_convert_b8x8<scalar_t, KV_DTYPE>(Klocalb8[d], k_scale);
}
}
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
dout[h] = gcn_mfma_instr<scalar_t, 4, 0, 0>(Qlocal[h].xy[0], Klocal[0].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 0, 0>(Qlocal[h].xy[1], Klocal[0].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 1, 0>(Qlocal[h].xy[0], Klocal[1].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 1, 0>(Qlocal[h].xy[1], Klocal[1].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 2, 0>(Qlocal[h].xy[0], Klocal[2].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 2, 0>(Qlocal[h].xy[1], Klocal[2].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 3, 0>(Qlocal[h].xy[0], Klocal[3].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 3, 0>(Qlocal[h].xy[1], Klocal[3].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 4, 0>(Qlocal[h].xy[0], Klocal[4].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 4, 0>(Qlocal[h].xy[1], Klocal[4].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 5, 0>(Qlocal[h].xy[0], Klocal[5].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 5, 0>(Qlocal[h].xy[1], Klocal[5].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 6, 0>(Qlocal[h].xy[0], Klocal[6].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 6, 0>(Qlocal[h].xy[1], Klocal[6].xy[1], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 7, 0>(Qlocal[h].xy[0], Klocal[7].xy[0], dout[h]);
dout[h] = gcn_mfma_instr<scalar_t, 4, 7, 0>(Qlocal[h].xy[1], Klocal[7].xy[1], dout[h]);
if constexpr(KHELOOP > 8)
{
dout[h] =
gcn_mfma_instr<scalar_t, 4, 8, 0>(Qlocal[h].xy[0], Klocal[8].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 8, 0>(Qlocal[h].xy[1], Klocal[8].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 9, 0>(Qlocal[h].xy[0], Klocal[9].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 9, 0>(Qlocal[h].xy[1], Klocal[9].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 10, 0>(Qlocal[h].xy[0], Klocal[10].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 10, 0>(Qlocal[h].xy[1], Klocal[10].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 11, 0>(Qlocal[h].xy[0], Klocal[11].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 11, 0>(Qlocal[h].xy[1], Klocal[11].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 12, 0>(Qlocal[h].xy[0], Klocal[12].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 12, 0>(Qlocal[h].xy[1], Klocal[12].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 13, 0>(Qlocal[h].xy[0], Klocal[13].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 13, 0>(Qlocal[h].xy[1], Klocal[13].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 14, 0>(Qlocal[h].xy[0], Klocal[14].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 14, 0>(Qlocal[h].xy[1], Klocal[14].xy[1], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 15, 0>(Qlocal[h].xy[0], Klocal[15].xy[0], dout[h]);
dout[h] =
gcn_mfma_instr<scalar_t, 4, 15, 0>(Qlocal[h].xy[1], Klocal[15].xy[1], dout[h]);
} // KHELOOP>8
dout[h] *= scale;
}
// transpose dout so that 4 token ids are in each lane, and 4 heads are across
// 4 lanes
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
// transpose dout so that 4 token ids are in each lane, and 4 heads are across
// 4 lanes
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
floatx4 tmp = {0};
#pragma unroll
for (int i = 0; i < 4; i++) {
#pragma unroll
for(int i = 0; i < 4; i++)
{
const float B = (lane4id == i) ? 1.0f : 0.0f;
// const float A = (global_token_idx < context_len) ? dout[h][i] : 0.0f;
tmp = __builtin_amdgcn_mfma_f32_4x4x1f32(dout[h][i], B, tmp, 0, 0, 0);
......@@ -539,50 +604,58 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const int lane4_token_idx = 4 * (global_token_idx >> 2);
const int alibi_offset = lane4_token_idx - context_len + 1;
if (alibi_slopes != nullptr) {
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for (int i = 0; i < 4; i++) {
if(alibi_slopes != nullptr)
{
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
#pragma unroll
for(int i = 0; i < 4; i++)
{
dout[h][i] += alibi_slope[h] * (alibi_offset + i);
}
}
}
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
qk_max[h] = -FLT_MAX;
#pragma unroll
for (int i = 0; i < 4; i++) {
qk_max[h] = (lane4_token_idx + i < context_len)
? fmaxf(qk_max[h], dout[h][i])
: qk_max[h];
}
#pragma unroll
for (int mask = WARP_SIZE / 2; mask >= 4; mask /= 2) {
#pragma unroll
for(int i = 0; i < 4; i++)
{
qk_max[h] =
(lane4_token_idx + i < context_len) ? fmaxf(qk_max[h], dout[h][i]) : qk_max[h];
}
#pragma unroll
for(int mask = WARP_SIZE / 2; mask >= 4; mask /= 2)
{
qk_max[h] = fmaxf(qk_max[h], __shfl_xor(qk_max[h], mask));
}
}
float exp_sum[QHLOOP];
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
exp_sum[h] = 0.0f;
#pragma unroll
for (int i = 0; i < 4; i++) {
dout[h][i] = (lane4_token_idx + i < context_len)
? __expf(dout[h][i] - qk_max[h])
: 0.0f;
#pragma unroll
for(int i = 0; i < 4; i++)
{
dout[h][i] =
(lane4_token_idx + i < context_len) ? __expf(dout[h][i] - qk_max[h]) : 0.0f;
exp_sum[h] += dout[h][i];
}
#pragma unroll
for (int mask = WARP_SIZE / 2; mask >= 4; mask /= 2) {
#pragma unroll
for(int mask = WARP_SIZE / 2; mask >= 4; mask /= 2)
{
exp_sum[h] += __shfl_xor(exp_sum[h], mask);
}
}
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
const int head_idx = 4 * h + lane4id;
shared_qk_max[warpid][head_idx] = qk_max[h];
shared_exp_sum[warpid][head_idx] = exp_sum[h];
......@@ -592,95 +665,86 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
__syncthreads();
const int num_heads = gridDim.z * GQA_RATIO;
float* max_logits_ptr =
max_logits + seq_idx * num_heads * max_num_partitions + partition_idx;
float* exp_sums_ptr =
exp_sums + seq_idx * num_heads * max_num_partitions + partition_idx;
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
float* max_logits_ptr = max_logits + seq_idx * num_heads * max_num_partitions + partition_idx;
float* exp_sums_ptr = exp_sums + seq_idx * num_heads * max_num_partitions + partition_idx;
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
float global_qk_max = -FLT_MAX;
float warp_qk_max[NWARPS];
const int head_idx = 4 * h + lane4id;
#pragma unroll
for (int w = 0; w < NWARPS; w++) {
#pragma unroll
for(int w = 0; w < NWARPS; w++)
{
warp_qk_max[w] = shared_qk_max[w][head_idx];
global_qk_max = fmaxf(global_qk_max, warp_qk_max[w]);
}
float global_exp_sum = 0.0f;
#pragma unroll
for (int w = 0; w < NWARPS; w++) {
global_exp_sum +=
shared_exp_sum[w][head_idx] * __expf(warp_qk_max[w] - global_qk_max);
}
if (head_idx < GQA_RATIO) {
max_logits_ptr[(wg_start_head_idx + head_idx) * max_num_partitions] =
global_qk_max;
exp_sums_ptr[(wg_start_head_idx + head_idx) * max_num_partitions] =
global_exp_sum;
}
const float global_inv_sum_scale = __fdividef(1.f, global_exp_sum + 1e-6f) *
__expf(qk_max[h] - global_qk_max);
#pragma unroll
for(int w = 0; w < NWARPS; w++)
{
global_exp_sum += shared_exp_sum[w][head_idx] * __expf(warp_qk_max[w] - global_qk_max);
}
if(head_idx < GQA_RATIO)
{
max_logits_ptr[(wg_start_head_idx + head_idx) * max_num_partitions] = global_qk_max;
exp_sums_ptr[(wg_start_head_idx + head_idx) * max_num_partitions] = global_exp_sum;
}
const float global_inv_sum_scale =
__fdividef(1.f, global_exp_sum + 1e-6f) * __expf(qk_max[h] - global_qk_max);
dout[h] *= global_inv_sum_scale;
}
// logits[h] -> every 4 lanes hold 4 heads, each lane holds 4 tokens, there
// are 4x16 tokens across warp
_B16x4 logits[QHLOOP];
#pragma unroll
for (int h = 0; h < QHLOOP; h++) {
#pragma unroll
for(int h = 0; h < QHLOOP; h++)
{
logits[h] = from_floatx4<scalar_t>(dout[h]);
}
__shared__ _B16x4 vout_shared[QHLOOP][VHELOOP][WARP_SIZE][NWARPS + 1];
if (warp_start_token_idx >= context_len) { // warp out of context
#pragma unroll
for (int qh = 0; qh < QHLOOP; qh++) {
#pragma unroll
for (int vh = 0; vh < VHELOOP; vh++) {
if(warp_start_token_idx >= context_len)
{ // warp out of context
#pragma unroll
for(int qh = 0; qh < QHLOOP; qh++)
{
#pragma unroll
for(int vh = 0; vh < VHELOOP; vh++)
{
vout_shared[qh][vh][laneid][warpid] = {0};
}
}
} else { // warp in context
// iterate across heads
#pragma unroll
for (int qh = 0; qh < QHLOOP; qh++) {
// iterate over each v head elem (within head_size)
#pragma unroll
for (int vh = 0; vh < VHELOOP; vh++) {
}
else
{ // warp in context
// iterate across heads
#pragma unroll
for(int qh = 0; qh < QHLOOP; qh++)
{
// iterate over each v head elem (within head_size)
#pragma unroll
for(int vh = 0; vh < VHELOOP; vh++)
{
floatx4 acc = {0};
// iterate over tokens
acc = gcn_mfma_instr<scalar_t, 4, 0, 0>(logits[qh], Vlocal[vh][0].xy[0],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 1, 0>(logits[qh], Vlocal[vh][0].xy[1],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 2, 0>(logits[qh], Vlocal[vh][1].xy[0],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 3, 0>(logits[qh], Vlocal[vh][1].xy[1],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 4, 0>(logits[qh], Vlocal[vh][2].xy[0],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 5, 0>(logits[qh], Vlocal[vh][2].xy[1],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 6, 0>(logits[qh], Vlocal[vh][3].xy[0],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 7, 0>(logits[qh], Vlocal[vh][3].xy[1],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 8, 0>(logits[qh], Vlocal[vh][4].xy[0],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 9, 0>(logits[qh], Vlocal[vh][4].xy[1],
acc);
acc = gcn_mfma_instr<scalar_t, 4, 10, 0>(logits[qh],
Vlocal[vh][5].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 11, 0>(logits[qh],
Vlocal[vh][5].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 12, 0>(logits[qh],
Vlocal[vh][6].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 13, 0>(logits[qh],
Vlocal[vh][6].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 14, 0>(logits[qh],
Vlocal[vh][7].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 15, 0>(logits[qh],
Vlocal[vh][7].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 0, 0>(logits[qh], Vlocal[vh][0].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 1, 0>(logits[qh], Vlocal[vh][0].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 2, 0>(logits[qh], Vlocal[vh][1].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 3, 0>(logits[qh], Vlocal[vh][1].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 4, 0>(logits[qh], Vlocal[vh][2].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 5, 0>(logits[qh], Vlocal[vh][2].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 6, 0>(logits[qh], Vlocal[vh][3].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 7, 0>(logits[qh], Vlocal[vh][3].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 8, 0>(logits[qh], Vlocal[vh][4].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 9, 0>(logits[qh], Vlocal[vh][4].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 10, 0>(logits[qh], Vlocal[vh][5].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 11, 0>(logits[qh], Vlocal[vh][5].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 12, 0>(logits[qh], Vlocal[vh][6].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 13, 0>(logits[qh], Vlocal[vh][6].xy[1], acc);
acc = gcn_mfma_instr<scalar_t, 4, 14, 0>(logits[qh], Vlocal[vh][7].xy[0], acc);
acc = gcn_mfma_instr<scalar_t, 4, 15, 0>(logits[qh], Vlocal[vh][7].xy[1], acc);
vout_shared[qh][vh][laneid][warpid] = from_floatx4<scalar_t>(acc);
}
}
......@@ -688,42 +752,48 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
__syncthreads();
if (warpid == 0) {
if(warpid == 0)
{
// const float out_scale = (fp8_out_scale_ptr != nullptr) ?
// __fdividef(1.0f,(*fp8_out_scale_ptr)) : 1.0f;
const float out_scale =
(fp8_out_scale_ptr != nullptr) ? 1.0f / (*fp8_out_scale_ptr) : 1.0f;
const float out_scale = (fp8_out_scale_ptr != nullptr) ? 1.0f / (*fp8_out_scale_ptr) : 1.0f;
_B16x4 vout[QHLOOP][VHELOOP];
// iterate across heads
#pragma unroll
for (int qh = 0; qh < QHLOOP; qh++) {
// iterate over each v head elem (within head_size)
#pragma unroll
for (int vh = 0; vh < VHELOOP; vh++) {
#pragma unroll
for(int qh = 0; qh < QHLOOP; qh++)
{
// iterate over each v head elem (within head_size)
#pragma unroll
for(int vh = 0; vh < VHELOOP; vh++)
{
vout[qh][vh] = {0};
#pragma unroll
for (int w = 0; w < NWARPS; w++) {
vout[qh][vh] =
addx4<scalar_t>(vout[qh][vh], vout_shared[qh][vh][laneid][w]);
#pragma unroll
for(int w = 0; w < NWARPS; w++)
{
vout[qh][vh] = addx4<scalar_t>(vout[qh][vh], vout_shared[qh][vh][laneid][w]);
}
}
}
if (context_len > partition_size) {
scalar_t* out_ptr = out +
seq_idx * num_heads * max_num_partitions * HEAD_SIZE +
if(context_len > partition_size)
{
scalar_t* out_ptr = out + seq_idx * num_heads * max_num_partitions * HEAD_SIZE +
partition_idx * HEAD_SIZE;
const int out_num_partitions = max_num_partitions;
bit16_t* out_ptr_b16 = reinterpret_cast<bit16_t*>(out_ptr);
#pragma unroll
for (int qh = 0; qh < QHLOOP; qh++) {
#pragma unroll
for (int vh = 0; vh < VHELOOP; vh++) {
#pragma unroll
for(int qh = 0; qh < QHLOOP; qh++)
{
#pragma unroll
for(int vh = 0; vh < VHELOOP; vh++)
{
const int head_size_elem = vh * WARP_SIZE + laneid;
#pragma unroll
for (int i = 0; i < 4; i++) {
#pragma unroll
for(int i = 0; i < 4; i++)
{
const int head_idx = 4 * qh + i;
if (head_idx < GQA_RATIO) {
if(head_idx < GQA_RATIO)
{
out_ptr_b16[(wg_start_head_idx + head_idx) * out_num_partitions *
HEAD_SIZE +
head_size_elem] = vout[qh][vh][i];
......@@ -732,31 +802,42 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
}
} // context_len > partition_size
else {
else
{
bit8_t* final_out_ptr_b8;
bit16_t* final_out_ptr_b16;
if constexpr (std::is_same<OUTT, bit8_t>::value) {
if constexpr(std::is_same<OUTT, bit8_t>::value)
{
final_out_ptr_b8 = final_out + seq_idx * num_heads * HEAD_SIZE;
} else {
}
else
{
OUTT* out_ptr = final_out + seq_idx * num_heads * HEAD_SIZE;
final_out_ptr_b16 = reinterpret_cast<bit16_t*>(out_ptr);
}
#pragma unroll
for (int qh = 0; qh < QHLOOP; qh++) {
#pragma unroll
for (int vh = 0; vh < VHELOOP; vh++) {
#pragma unroll
for(int qh = 0; qh < QHLOOP; qh++)
{
#pragma unroll
for(int vh = 0; vh < VHELOOP; vh++)
{
const int head_size_elem = vh * WARP_SIZE + laneid;
#pragma unroll
for (int i = 0; i < 4; i++) {
#pragma unroll
for(int i = 0; i < 4; i++)
{
const int head_idx = 4 * qh + i;
if (head_idx < GQA_RATIO) {
if constexpr (std::is_same<OUTT, bit8_t>::value) {
if(head_idx < GQA_RATIO)
{
if constexpr(std::is_same<OUTT, bit8_t>::value)
{
const float tmpf =
out_scale * to_float_b16<scalar_t>(vout[qh][vh][i]);
const OUTT tmp = hip_fp8(tmpf).data;
final_out_ptr_b8[(wg_start_head_idx + head_idx) * HEAD_SIZE +
head_size_elem] = tmp;
} else {
}
else
{
final_out_ptr_b16[(wg_start_head_idx + head_idx) * HEAD_SIZE +
head_size_elem] = vout[qh][vh][i];
}
......@@ -769,10 +850,13 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
}
// Grid: (num_heads, num_seqs).
template <typename scalar_t, typename OUTT, int HEAD_SIZE, int NUM_THREADS,
int PARTITION_SIZE, int NPAR_LOOPS>
__global__
__launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
template <typename scalar_t,
typename OUTT,
int HEAD_SIZE,
int NUM_THREADS,
int PARTITION_SIZE,
int NPAR_LOOPS>
__global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
OUTT* __restrict__ out, // [num_seqs, num_heads, head_size]
const float* __restrict__ exp_sums, // [num_seqs, num_heads,
// max_num_partitions]
......@@ -781,13 +865,16 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
const scalar_t* __restrict__ tmp_out, // [num_seqs, num_heads,
// max_num_partitions, head_size]
const int* __restrict__ context_lens, // [num_seqs]
const int max_num_partitions, const float* __restrict__ fp8_out_scale_ptr) {
const int max_num_partitions,
const float* __restrict__ fp8_out_scale_ptr)
{
const int num_heads = gridDim.x;
const int head_idx = blockIdx.x;
const int seq_idx = blockIdx.y;
const int context_len = context_lens[seq_idx];
const int num_partitions = DIVIDE_ROUND_UP(context_len, PARTITION_SIZE);
if (num_partitions == 1) {
if(num_partitions == 1)
{
// if num_partitions==1, main kernel will write to out directly, no work in
// reduction kernel
return;
......@@ -801,10 +888,10 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
// max num partitions supported is warp_size * NPAR_LOOPS
__shared__ float shared_exp_sums[NPAR_LOOPS * WARP_SIZE];
if (warpid == 0) {
const float* max_logits_ptr = max_logits +
seq_idx * num_heads * max_num_partitions +
head_idx * max_num_partitions;
if(warpid == 0)
{
const float* max_logits_ptr =
max_logits + seq_idx * num_heads * max_num_partitions + head_idx * max_num_partitions;
// valid partition is the last valid partition in case threadid > num
// partitions
......@@ -812,70 +899,78 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
float reg_max_logit[NPAR_LOOPS];
const int last_valid_partition = num_partitions - 1;
#pragma unroll
for (int i = 0; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 0; i < NPAR_LOOPS; i++)
{
const int partition_no = i * WARP_SIZE + threadIdx.x;
valid_partition[i] =
(partition_no < num_partitions) ? partition_no : last_valid_partition;
}
#pragma unroll
for (int i = 0; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 0; i < NPAR_LOOPS; i++)
{
reg_max_logit[i] = max_logits_ptr[valid_partition[i]];
}
float max_logit = reg_max_logit[0];
#pragma unroll
for (int i = 1; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 1; i < NPAR_LOOPS; i++)
{
max_logit = fmaxf(max_logit, reg_max_logit[i]);
}
#pragma unroll
for (int mask = WARP_SIZE / 2; mask >= 1; mask /= 2) {
#pragma unroll
for(int mask = WARP_SIZE / 2; mask >= 1; mask /= 2)
{
max_logit = fmaxf(max_logit, __shfl_xor(max_logit, mask));
}
const float* exp_sums_ptr = exp_sums +
seq_idx * num_heads * max_num_partitions +
head_idx * max_num_partitions;
const float* exp_sums_ptr =
exp_sums + seq_idx * num_heads * max_num_partitions + head_idx * max_num_partitions;
float rescaled_exp_sum[NPAR_LOOPS];
#pragma unroll
for (int i = 0; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 0; i < NPAR_LOOPS; i++)
{
rescaled_exp_sum[i] = exp_sums_ptr[valid_partition[i]];
}
#pragma unroll
for (int i = 0; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 0; i < NPAR_LOOPS; i++)
{
const int partition_no = i * WARP_SIZE + threadIdx.x;
rescaled_exp_sum[i] *= (partition_no < num_partitions)
? expf(reg_max_logit[i] - max_logit)
: 0.0f;
rescaled_exp_sum[i] *=
(partition_no < num_partitions) ? expf(reg_max_logit[i] - max_logit) : 0.0f;
}
float global_exp_sum = rescaled_exp_sum[0];
#pragma unroll
for (int i = 1; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 1; i < NPAR_LOOPS; i++)
{
global_exp_sum += rescaled_exp_sum[i];
}
#pragma unroll
for (int i = 0; i < NPAR_LOOPS; i++) {
#pragma unroll
for(int i = 0; i < NPAR_LOOPS; i++)
{
const int partition_no = i * WARP_SIZE + threadIdx.x;
shared_exp_sums[partition_no] = rescaled_exp_sum[i];
}
#pragma unroll
for (int mask = WARP_SIZE / 2; mask >= 1; mask /= 2) {
#pragma unroll
for(int mask = WARP_SIZE / 2; mask >= 1; mask /= 2)
{
global_exp_sum += __shfl_xor(global_exp_sum, mask);
}
if (threadIdx.x == 0) {
if(threadIdx.x == 0)
{
shared_global_exp_sum = global_exp_sum;
}
} // warpid == 0
const scalar_t* tmp_out_ptr =
tmp_out + seq_idx * num_heads * max_num_partitions * HEAD_SIZE +
const scalar_t* tmp_out_ptr = tmp_out + seq_idx * num_heads * max_num_partitions * HEAD_SIZE +
head_idx * max_num_partitions * HEAD_SIZE + threadIdx.x;
constexpr int MAX_NPAR = 64;
scalar_t tmps[MAX_NPAR];
const float dzero = 0.0f;
#pragma unroll
for (int j = 0; j < MAX_NPAR; j++) {
#pragma unroll
for(int j = 0; j < MAX_NPAR; j++)
{
tmps[j] = from_float<scalar_t>(dzero);
}
const int last_partition_offset = (num_partitions - 1) * HEAD_SIZE;
......@@ -884,32 +979,32 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
constexpr int JCHUNK = 16;
#pragma unroll
for (int j = 0; j < JCHUNK * HEAD_SIZE; j += HEAD_SIZE) {
#pragma unroll
for(int j = 0; j < JCHUNK * HEAD_SIZE; j += HEAD_SIZE)
{
// lastj is last valid partition
const int lastj_offset =
(j < num_partition_offset) ? j : last_partition_offset;
const int lastj_offset = (j < num_partition_offset) ? j : last_partition_offset;
tmps[idx] = tmp_out_ptr[lastj_offset];
idx++;
}
__syncthreads();
if (num_partitions > JCHUNK) {
#pragma unroll
for (int j = JCHUNK * HEAD_SIZE; j < 2 * JCHUNK * HEAD_SIZE;
j += HEAD_SIZE) {
const int lastj_offset =
(j < num_partition_offset) ? j : last_partition_offset;
if(num_partitions > JCHUNK)
{
#pragma unroll
for(int j = JCHUNK * HEAD_SIZE; j < 2 * JCHUNK * HEAD_SIZE; j += HEAD_SIZE)
{
const int lastj_offset = (j < num_partition_offset) ? j : last_partition_offset;
tmps[idx] = tmp_out_ptr[lastj_offset];
idx++;
}
if (num_partitions > 2 * JCHUNK) {
#pragma unroll
for (int j = 2 * JCHUNK * HEAD_SIZE; j < MAX_NPAR * HEAD_SIZE;
j += HEAD_SIZE) {
const int lastj_offset =
(j < num_partition_offset) ? j : last_partition_offset;
if(num_partitions > 2 * JCHUNK)
{
#pragma unroll
for(int j = 2 * JCHUNK * HEAD_SIZE; j < MAX_NPAR * HEAD_SIZE; j += HEAD_SIZE)
{
const int lastj_offset = (j < num_partition_offset) ? j : last_partition_offset;
tmps[idx] = tmp_out_ptr[lastj_offset];
idx++;
}
......@@ -918,64 +1013,77 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
// Aggregate tmp_out to out.
float acc = 0.0f;
#pragma unroll
for (int j = 0; j < JCHUNK; j++) {
#pragma unroll
for(int j = 0; j < JCHUNK; j++)
{
acc += to_float<scalar_t>(tmps[j]) * shared_exp_sums[j];
}
if (num_partitions > JCHUNK) {
#pragma unroll
for (int j = JCHUNK; j < 2 * JCHUNK; j++) {
if(num_partitions > JCHUNK)
{
#pragma unroll
for(int j = JCHUNK; j < 2 * JCHUNK; j++)
{
acc += to_float<scalar_t>(tmps[j]) * shared_exp_sums[j];
}
if (num_partitions > 2 * JCHUNK) {
#pragma unroll
for (int j = 2 * JCHUNK; j < MAX_NPAR; j++) {
if(num_partitions > 2 * JCHUNK)
{
#pragma unroll
for(int j = 2 * JCHUNK; j < MAX_NPAR; j++)
{
acc += to_float<scalar_t>(tmps[j]) * shared_exp_sums[j];
}
}
}
for (int p = 1; p < NPAR_LOOPS; p++) {
if (num_partitions > p * MAX_NPAR) {
for(int p = 1; p < NPAR_LOOPS; p++)
{
if(num_partitions > p * MAX_NPAR)
{
idx = 0;
#pragma unroll
for (int j = p * MAX_NPAR * HEAD_SIZE; j < (p + 1) * MAX_NPAR * HEAD_SIZE;
j += HEAD_SIZE) {
#pragma unroll
for(int j = p * MAX_NPAR * HEAD_SIZE; j < (p + 1) * MAX_NPAR * HEAD_SIZE;
j += HEAD_SIZE)
{
// lastj is last valid partition
const int lastj_offset =
(j < num_partition_offset) ? j : last_partition_offset;
const int lastj_offset = (j < num_partition_offset) ? j : last_partition_offset;
tmps[idx] = tmp_out_ptr[lastj_offset];
idx++;
}
#pragma unroll
for (int j = 0; j < MAX_NPAR; j++) {
#pragma unroll
for(int j = 0; j < MAX_NPAR; j++)
{
acc += to_float<scalar_t>(tmps[j]) * shared_exp_sums[j + p * MAX_NPAR];
}
}
}
const float inv_global_exp_sum =
__fdividef(1.0f, shared_global_exp_sum + 1e-6f);
const float inv_global_exp_sum = __fdividef(1.0f, shared_global_exp_sum + 1e-6f);
// const float out_scale = (fp8_out_scale_ptr != nullptr) ?
// __fdividef(1.0f,(*fp8_out_scale_ptr)) : 1.0f;
const float out_scale =
(fp8_out_scale_ptr != nullptr) ? 1.0f / (*fp8_out_scale_ptr) : 1.0f;
const float out_scale = (fp8_out_scale_ptr != nullptr) ? 1.0f / (*fp8_out_scale_ptr) : 1.0f;
acc *= inv_global_exp_sum;
acc *= out_scale;
OUTT* out_ptr = out + seq_idx * num_heads * HEAD_SIZE + head_idx * HEAD_SIZE;
if constexpr (std::is_same<OUTT, bit8_t>::value) {
if constexpr(std::is_same<OUTT, bit8_t>::value)
{
out_ptr[threadIdx.x] = hip_fp8(acc).data;
} else {
}
else
{
out_ptr[threadIdx.x] = from_float<scalar_t>(acc);
}
}
#else // !defined(__HIP__MI300_MI250__) TODO: Add NAVI support
template <typename scalar_t, typename cache_t,
vllm::Fp8KVCacheDataType KV_DTYPE, typename OUTT, int BLOCK_SIZE,
int HEAD_SIZE, int NUM_THREADS,
template <typename scalar_t,
typename cache_t,
vllm::Fp8KVCacheDataType KV_DTYPE,
typename OUTT,
int BLOCK_SIZE,
int HEAD_SIZE,
int NUM_THREADS,
int GQA_RATIO>
__global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
const scalar_t* __restrict__ q, // [num_seqs, num_heads, head_size]
......@@ -983,28 +1091,37 @@ __global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_QKV_kernel(
// head_size/x, block_size, x]
const cache_t* __restrict__ v_cache, // [num_blocks, num_kv_heads,
// head_size, block_size]
const int num_kv_heads, const float scale,
const int num_kv_heads,
const float scale,
const int* __restrict__ block_tables, // [num_seqs, max_num_blocks_per_seq]
const int* __restrict__ context_lens, // [num_seqs]
const int max_num_blocks_per_seq,
const float* __restrict__ alibi_slopes, // [num_heads]
const int q_stride, const int kv_block_stride, const int kv_head_stride,
const int q_stride,
const int kv_block_stride,
const int kv_head_stride,
float* __restrict__ exp_sums, // [num_seqs, num_heads, max_num_partitions]
float* __restrict__ max_logits, // [num_seqs, num_heads,
// max_num_partitions]
scalar_t* __restrict__ out, // [num_seqs, num_heads, max_num_partitions,
// head_size]
OUTT* __restrict__ final_out, // [num_seqs, num_heads, head_size]
int max_ctx_blocks, float k_scale, float v_scale,
const float* __restrict__ fp8_out_scale_ptr) {
int max_ctx_blocks,
float k_scale,
float v_scale,
const float* __restrict__ fp8_out_scale_ptr)
{
UNREACHABLE_CODE
}
// Grid: (num_heads, num_seqs).
template <typename scalar_t, typename OUTT, int HEAD_SIZE, int NUM_THREADS,
int PARTITION_SIZE, int NPAR_LOOPS>
__global__
__launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
template <typename scalar_t,
typename OUTT,
int HEAD_SIZE,
int NUM_THREADS,
int PARTITION_SIZE,
int NPAR_LOOPS>
__global__ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
OUTT* __restrict__ out, // [num_seqs, num_heads, head_size]
const float* __restrict__ exp_sums, // [num_seqs, num_heads,
// max_num_partitions]
......@@ -1014,6 +1131,9 @@ __launch_bounds__(NUM_THREADS) void paged_attention_ll4mi_reduce_kernel(
// max_num_partitions, head_size]
const int* __restrict__ context_lens, // [num_seqs]
const int max_num_partitions,
const float* __restrict__ fp8_out_scale_ptr){UNREACHABLE_CODE}
const float* __restrict__ fp8_out_scale_ptr)
{
UNREACHABLE_CODE
}
#endif // defined(__HIP__MI300_MI250__) TODO: Add NAVI support
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