submission 252223
basesearch · python · License unknown
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Vendorable · source mirrored · license unknownView source →
No package. Vendor the mirrored source: 1397 lines, June 9 Researcher Reciprocity License v1.0.
result.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-nvfp4-dual-gemm-252223?include=source"interfacepython
Compatibility
measured onNVIDIA B200
declared hardwareNVIDIA B200
architecturessm_100
dtypesfp8_e4m3, nvfp4
Benchmark evidence
1 measurement across 1 GPU, fastest first.
Operation / workload
Hardware
Latency
Rank
Observed
Reported · How evidence levels are derived →
Source and license
sourceavailable
revision digestsha256:42985cce4f0c5991bf385170dbcdf0d527cce12ef2376ced6ba4988956fd47d6
license declaredunknown
license concludedunknown
authorsbasesearch
imported2026-08-15
Techniques
Extracted from the mirrored source by pattern, never inferred. Each row cites its line.
cluster
__global__ __cluster_dims__(2, 1, 1) __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)mbarrier
__device__ __forceinline__ void mbarrier_init(int mbar_addr, int count) {shared-memory
__device__ __forceinline__ void tma_3d_gmem2smem_cluster2(int dst, const void *tmap_ptr, int x, int y, int z, int mbar_addr, uint64_t cache_policy) {tcgen05
asm volatile("tcgen05.cp.cta_group::1.32x128b.warpx4 [%0], %1;" :: "r"(taddr), "l"(s_desc));tma
"cp.async.bulk.shared::cta.global.mbarrier::complete_tx::bytes.L2::cache_hint "vector-width = float2
reinterpret_cast<float2 *>(C_ptr + (row + 0) * N + col)[0] = float2{tmp[i * 4 + 0], tmp[i * 4 + 1]};Kernel source
result.py1397 lines
#!POPCORN leaderboard nvfp4_dual_gemm
#!POPCORN gpu NVIDIA
import torch
from torch.utils.cpp_extension import load_inline
_CUDA_SRC = r"""
#include <cuda.h>
#include <cudaTypedefs.h>
#include <cuda_fp16.h>
#include <cuda_runtime.h>
#include <torch/library.h>
#include <ATen/core/Tensor.h>
constexpr int WARP_SIZE = 32;
constexpr int MMA_K = 64;
constexpr uint64_t EVICT_FIRST = 0x12F0000000000000ULL;
constexpr uint64_t EVICT_LAST = 0x14F0000000000000ULL;
constexpr uint32_t PEER_MASK = 0xFEFFFFFFU;
__device__ __forceinline__ constexpr uint64_t desc_encode(uint64_t x) { return (x & 0x3'FFFFULL) >> 4ULL; }
__device__ __forceinline__ uint32_t elect_sync() {
uint32_t pred = 0;
asm volatile(
"{\n\t"
".reg .pred %%px;\n\t"
"elect.sync _|%%px, %1;\n\t"
"@%%px mov.s32 %0, 1;\n\t"
"}\n\t"
: "+r"(pred)
: "r"(0xFFFFFFFF)
);
return pred;
}
__device__ __forceinline__ void mbarrier_init(int mbar_addr, int count) {
asm volatile("mbarrier.init.shared::cta.b64 [%0], %1;" :: "r"(mbar_addr), "r"(count));
}
__device__ __forceinline__ void mbarrier_wait(int mbar_addr, int phase) {
uint32_t ticks = 0x989680;
asm volatile(
"{\n\t"
".reg .pred P1;\n\t"
"LAB_WAIT:\n\t"
"mbarrier.try_wait.parity.acquire.cta.shared::cta.b64 P1, [%0], %1, %2;\n\t"
"@P1 bra.uni DONE;\n\t"
"bra.uni LAB_WAIT;\n\t"
"DONE:\n\t"
"}\n\t"
:: "r"(mbar_addr), "r"(phase), "r"(ticks)
);
}
__device__ __forceinline__ void tma_gmem2smem(int dst, const void *src, int size, int mbar_addr, uint64_t cache_policy) {
asm volatile(
"cp.async.bulk.shared::cta.global.mbarrier::complete_tx::bytes.L2::cache_hint "
"[%0], [%1], %2, [%3], %4;"
:: "r"(dst), "l"(src), "r"(size), "r"(mbar_addr), "l"(cache_policy)
);
}
__device__ __forceinline__ void tma_3d_gmem2smem(int dst, const void *tmap_ptr, int x, int y, int z, int mbar_addr, uint64_t cache_policy) {
asm volatile(
"cp.async.bulk.tensor.3d.shared::cta.global.mbarrier::complete_tx::bytes.cta_group::1.L2::cache_hint "
"[%0], [%1, {%2, %3, %4}], [%5], %6;"
:: "r"(dst), "l"(tmap_ptr), "r"(x), "r"(y), "r"(z), "r"(mbar_addr), "l"(cache_policy)
: "memory"
);
}
__device__ __forceinline__ void tma_3d_gmem2smem_cluster2(int dst, const void *tmap_ptr, int x, int y, int z, int mbar_addr, uint64_t cache_policy) {
asm volatile(
"cp.async.bulk.tensor.3d.cta_group::2.shared::cluster.global.mbarrier::complete_tx::bytes.L2::cache_hint "
"[%0], [%1, {%2, %3, %4}], [%5], %6;"
:: "r"(dst), "l"(tmap_ptr), "r"(x), "r"(y), "r"(z), "r"(mbar_addr), "l"(cache_policy)
: "memory"
);
}
__device__ __forceinline__ void tcgen05_cp_nvfp4(int taddr, uint64_t s_desc) {
asm volatile("tcgen05.cp.cta_group::1.32x128b.warpx4 [%0], %1;" :: "r"(taddr), "l"(s_desc));
}
__device__ __forceinline__ void tcgen05_mma_nvfp4(
int d_tmem,
uint64_t a_desc,
uint64_t b_desc,
uint32_t i_desc,
int scale_A_tmem,
int scale_B_tmem,
int enable_input_d
) {
asm volatile(
"{\n\t"
".reg .pred p;\n\t"
"setp.ne.b32 p, %6, 0;\n\t"
"tcgen05.mma.cta_group::1.kind::mxf4nvf4.block_scale.block16 [%0], %1, %2, %3, [%4], [%5], p;\n\t"
"}\n\t"
:: "r"(d_tmem), "l"(a_desc), "l"(b_desc), "r"(i_desc),
"r"(scale_A_tmem), "r"(scale_B_tmem), "r"(enable_input_d)
);
}
struct SHAPE { static constexpr char _16x256b[] = ".16x256b"; };
struct NUM { static constexpr char x8[] = ".x8"; };
template <const char *SHAPE_, const char *NUM_>
__device__ __forceinline__ void tcgen05_ld_32regs(float *tmp, int row, int col) {
asm volatile(
"tcgen05.ld.sync.aligned%33%34.b32 "
"{ %0, %1, %2, %3, %4, %5, %6, %7, "
" %8, %9, %10, %11, %12, %13, %14, %15, "
" %16, %17, %18, %19, %20, %21, %22, %23, "
" %24, %25, %26, %27, %28, %29, %30, %31}, [%32];"
: "=f"(tmp[ 0]), "=f"(tmp[ 1]), "=f"(tmp[ 2]), "=f"(tmp[ 3]), "=f"(tmp[ 4]), "=f"(tmp[ 5]), "=f"(tmp[ 6]), "=f"(tmp[ 7]),
"=f"(tmp[ 8]), "=f"(tmp[ 9]), "=f"(tmp[10]), "=f"(tmp[11]), "=f"(tmp[12]), "=f"(tmp[13]), "=f"(tmp[14]), "=f"(tmp[15]),
"=f"(tmp[16]), "=f"(tmp[17]), "=f"(tmp[18]), "=f"(tmp[19]), "=f"(tmp[20]), "=f"(tmp[21]), "=f"(tmp[22]), "=f"(tmp[23]),
"=f"(tmp[24]), "=f"(tmp[25]), "=f"(tmp[26]), "=f"(tmp[27]), "=f"(tmp[28]), "=f"(tmp[29]), "=f"(tmp[30]), "=f"(tmp[31])
: "r"((row << 16) | col), "C"(SHAPE_), "C"(NUM_)
);
}
__device__ __forceinline__ void tcgen05_ld_16x256bx8(float *tmp, int row, int col) {
tcgen05_ld_32regs<SHAPE::_16x256b, NUM::x8>(tmp, row, col);
}
__device__ __forceinline__ float exp2_approx(float x) {
float y;
asm("ex2.approx.f32 %0, %1;" : "=f"(y) : "f"(x));
return y;
}
__device__ __forceinline__ float sigmoid_fast(float x) {
const float t = exp2_approx(-x * 1.4426950408889634f);
return __fdividef(1.0f, 1.0f + t);
}
static inline void ck_cu(CUresult err) {
if (err == CUDA_SUCCESS) return;
const char *msg = nullptr;
if (cuGetErrorString(err, &msg) != CUDA_SUCCESS) msg = "cu err";
TORCH_CHECK(false, msg);
}
static inline void init_AB_tmap(
CUtensorMap *tmap,
const char *ptr,
uint64_t global_h, uint64_t global_w,
uint32_t shared_h, uint32_t shared_w
) {
constexpr uint32_t rank = 3;
uint64_t globalDim[rank] = {256, global_h, global_w / 256};
uint64_t globalStrides[rank-1] = {global_w / 2, 128};
uint32_t boxDim[rank] = {256, shared_h, shared_w / 256};
uint32_t elementStrides[rank] = {1, 1, 1};
auto err = cuTensorMapEncodeTiled(
tmap,
CUtensorMapDataType::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B,
rank,
(void *)ptr,
globalDim,
globalStrides,
boxDim,
elementStrides,
CUtensorMapInterleave::CU_TENSOR_MAP_INTERLEAVE_NONE,
CUtensorMapSwizzle::CU_TENSOR_MAP_SWIZZLE_128B,
CUtensorMapL2promotion::CU_TENSOR_MAP_L2_PROMOTION_NONE,
CUtensorMapFloatOOBfill::CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE
);
ck_cu(err);
}
struct TmapCache {
const char *ptr = nullptr;
uint64_t global_h = 0;
uint64_t global_w = 0;
uint32_t shared_h = 0;
uint32_t shared_w = 0;
bool valid = false;
CUtensorMap tmap;
inline CUtensorMap get(const char *p, uint64_t gh, uint64_t gw, uint32_t sh, uint32_t sw) {
if (valid && ptr == p && global_h == gh && global_w == gw && shared_h == sh && shared_w == sw) return tmap;
init_AB_tmap(&tmap, p, gh, gw, sh, sw);
ptr = p;
global_h = gh;
global_w = gw;
shared_h = sh;
shared_w = sw;
valid = true;
return tmap;
}
};
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
__global__ __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)
void gemm_f32_kernel(
const __grid_constant__ CUtensorMap A_tmap,
const __grid_constant__ CUtensorMap B_tmap,
const char *SFA_ptr,
const char *SFB_ptr,
float *C_ptr,
int M, int N
) {
const int tid = threadIdx.x;
const int bid = blockIdx.y;
const int lane_id = tid & 31;
const int warp_id = tid >> 5;
const int grid_n = N / BLOCK_N;
const int bid_m = bid / grid_n;
const int bid_n = bid - bid_m * grid_n;
const int off_m = bid_m * BLOCK_M;
const int off_n = bid_n * BLOCK_N;
constexpr int NUM_WARPS = BLOCK_M / WARP_SIZE + 2;
extern __shared__ __align__(1024) char smem_ptr[];
const int smem = static_cast<int>(__cvta_generic_to_shared(smem_ptr));
constexpr int A_size = BLOCK_M * BLOCK_K / 2;
constexpr int B_size = BLOCK_N * BLOCK_K / 2;
constexpr int SFA_size = 128 * BLOCK_K / 16;
constexpr int SFB_size = 128 * BLOCK_K / 16;
constexpr int STAGE_SIZE = A_size + B_size + SFA_size + SFB_size;
#pragma nv_diag_suppress static_var_with_dynamic_init
__shared__ int64_t mbars[NUM_STAGES * 2 + 1];
const int tma_mbar_addr = static_cast<int>(__cvta_generic_to_shared(mbars));
const int mma_mbar_addr = tma_mbar_addr + NUM_STAGES * 8;
const int mainloop_mbar_addr = mma_mbar_addr + NUM_STAGES * 8;
constexpr int SFA_tmem = BLOCK_N;
constexpr int SFB_tmem = SFA_tmem + 4 * (BLOCK_K / MMA_K);
if (warp_id == 0 && elect_sync()) {
for (int i = 0; i < NUM_STAGES * 2 + 1; i++) mbarrier_init(tma_mbar_addr + i * 8, 1);
asm volatile("fence.mbarrier_init.release.cluster;");
} else if (warp_id == 1) {
asm volatile("tcgen05.alloc.cta_group::1.sync.aligned.shared::cta.b32 [%0], %1;" :: "r"(smem), "r"(BLOCK_N * 2));
}
__syncthreads();
constexpr int num_iters = K / BLOCK_K;
if (warp_id == NUM_WARPS - 2 && elect_sync()) {
const uint64_t cache_A = EVICT_FIRST;
const uint64_t cache_B = EVICT_FIRST;
auto issue_tma = [&](int iter_k, int stage_id) {
const int mbar_addr = tma_mbar_addr + stage_id * 8;
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B_smem = A_smem + A_size;
const int SFA_smem = B_smem + B_size;
const int SFB_smem = SFA_smem + SFA_size;
const int off_k = iter_k * BLOCK_K;
tma_3d_gmem2smem(A_smem, &A_tmap, 0, off_m, off_k / 256, mbar_addr, cache_A);
tma_3d_gmem2smem(B_smem, &B_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
const int rest_k = K / 16 / 4;
const char *SFA_src = SFA_ptr + ((off_m / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB_src = SFB_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
tma_gmem2smem(SFA_smem, SFA_src, SFA_size, mbar_addr, cache_A);
tma_gmem2smem(SFB_smem, SFB_src, SFB_size, mbar_addr, cache_B);
asm volatile(
"mbarrier.arrive.expect_tx.release.cta.shared::cta.b64 _, [%0], %1;"
:: "r"(mbar_addr), "r"(STAGE_SIZE)
: "memory"
);
};
constexpr int PRELOAD = (num_iters < NUM_STAGES) ? num_iters : NUM_STAGES;
for (int iter_k = 0; iter_k < PRELOAD; iter_k++) issue_tma(iter_k, iter_k);
for (int iter_k = NUM_STAGES; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int mma_phase = (iter_k / NUM_STAGES - 1) & 1;
mbarrier_wait(mma_mbar_addr + stage_id * 8, mma_phase);
issue_tma(iter_k, stage_id);
}
} else if (warp_id == NUM_WARPS - 1 && elect_sync()) {
constexpr int MMA_N = BLOCK_N;
constexpr int MMA_M = 128;
constexpr uint32_t i_desc = (1U << 7U) | (1U << 10U) | ((uint32_t)MMA_N >> 3U << 17U) | ((uint32_t)MMA_M >> 7U << 27U);
for (int iter_k = 0; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int tma_phase = (iter_k / NUM_STAGES) & 1;
mbarrier_wait(tma_mbar_addr + stage_id * 8, tma_phase);
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B_smem = A_smem + A_size;
const int SFA_smem = B_smem + B_size;
const int SFB_smem = SFA_smem + SFA_size;
auto make_desc_AB = [](int addr) -> uint64_t {
const int SBO = 8 * 128;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL) | (2ULL << 61ULL);
};
auto make_desc_SF = [](int addr) -> uint64_t {
const int SBO = 8 * 16;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL);
};
constexpr uint64_t SF_desc = make_desc_SF(0);
const uint64_t SFA_desc = SF_desc + ((uint64_t)SFA_smem >> 4ULL);
const uint64_t SFB_desc = SF_desc + ((uint64_t)SFB_smem >> 4ULL);
for (int k = 0; k < BLOCK_K / MMA_K; k++) {
uint64_t sfa_desc = SFA_desc + (uint64_t)k * (512ULL >> 4ULL);
uint64_t sfb_desc = SFB_desc + (uint64_t)k * (512ULL >> 4ULL);
tcgen05_cp_nvfp4(SFA_tmem + k * 4, sfa_desc);
tcgen05_cp_nvfp4(SFB_tmem + k * 4, sfb_desc);
}
for (int k1 = 0; k1 < BLOCK_K / 256; k1++)
for (int k2 = 0; k2 < 256 / MMA_K; k2++) {
uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);
uint64_t b_desc = make_desc_AB(B_smem + k1 * BLOCK_N * 128 + k2 * 32);
const int k_sf = k1 * 4 + k2;
const int scale_A_tmem = SFA_tmem + k_sf * 4;
const int scale_B_tmem = SFB_tmem + k_sf * 4 + (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);
const int enable_input_d = (k1 == 0 && k2 == 0) ? iter_k : 1;
tcgen05_mma_nvfp4(0, a_desc, b_desc, i_desc, scale_A_tmem, scale_B_tmem, enable_input_d);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mma_mbar_addr + stage_id * 8)
: "memory"
);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mainloop_mbar_addr)
: "memory"
);
} else if (tid < BLOCK_M) {
mbarrier_wait(mainloop_mbar_addr, 0);
asm volatile("tcgen05.fence::after_thread_sync;");
for (int mm = 0; mm < 2; mm++) {
float tmp[BLOCK_N / 2];
tcgen05_ld_16x256bx8(tmp, warp_id * 32 + mm * 16, 0);
if constexpr (BLOCK_N == 128) tcgen05_ld_16x256bx8(tmp + 32, warp_id * 32 + mm * 16, 64);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < BLOCK_N / 8; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + i * 8 + (lane_id & 3) * 2;
reinterpret_cast<float2 *>(C_ptr + (row + 0) * N + col)[0] = float2{tmp[i * 4 + 0], tmp[i * 4 + 1]};
reinterpret_cast<float2 *>(C_ptr + (row + 8) * N + col)[0] = float2{tmp[i * 4 + 2], tmp[i * 4 + 3]};
}
}
asm volatile("bar.sync 1, %0;" :: "r"(BLOCK_M) : "memory");
if (warp_id == 0) asm volatile("tcgen05.dealloc.cta_group::1.sync.aligned.b32 %0, %1;" :: "r"(0), "r"(BLOCK_N * 2));
}
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
__global__ __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)
void gemm_silu_mul_kernel(
const __grid_constant__ CUtensorMap A_tmap,
const __grid_constant__ CUtensorMap B_tmap,
const char *SFA_ptr,
const char *SFB_ptr,
const float *G1_ptr,
half *Out_ptr,
int M, int N
) {
const int tid = threadIdx.x;
const int bid = blockIdx.y;
const int lane_id = tid & 31;
const int warp_id = tid >> 5;
const int grid_n = N / BLOCK_N;
const int bid_m = bid / grid_n;
const int bid_n = bid - bid_m * grid_n;
const int off_m = bid_m * BLOCK_M;
const int off_n = bid_n * BLOCK_N;
constexpr int NUM_WARPS = BLOCK_M / WARP_SIZE + 2;
extern __shared__ __align__(1024) char smem_ptr[];
const int smem = static_cast<int>(__cvta_generic_to_shared(smem_ptr));
constexpr int A_size = BLOCK_M * BLOCK_K / 2;
constexpr int B_size = BLOCK_N * BLOCK_K / 2;
constexpr int SFA_size = 128 * BLOCK_K / 16;
constexpr int SFB_size = 128 * BLOCK_K / 16;
constexpr int STAGE_SIZE = A_size + B_size + SFA_size + SFB_size;
#pragma nv_diag_suppress static_var_with_dynamic_init
__shared__ int64_t mbars[NUM_STAGES * 2 + 1];
const int tma_mbar_addr = static_cast<int>(__cvta_generic_to_shared(mbars));
const int mma_mbar_addr = tma_mbar_addr + NUM_STAGES * 8;
const int mainloop_mbar_addr = mma_mbar_addr + NUM_STAGES * 8;
constexpr int SFA_tmem = BLOCK_N;
constexpr int SFB_tmem = SFA_tmem + 4 * (BLOCK_K / MMA_K);
if (warp_id == 0 && elect_sync()) {
for (int i = 0; i < NUM_STAGES * 2 + 1; i++) mbarrier_init(tma_mbar_addr + i * 8, 1);
asm volatile("fence.mbarrier_init.release.cluster;");
} else if (warp_id == 1) {
asm volatile("tcgen05.alloc.cta_group::1.sync.aligned.shared::cta.b32 [%0], %1;" :: "r"(smem), "r"(BLOCK_N * 2));
}
__syncthreads();
constexpr int num_iters = K / BLOCK_K;
if (warp_id == NUM_WARPS - 2 && elect_sync()) {
const uint64_t cache_A = EVICT_FIRST;
const uint64_t cache_B = EVICT_FIRST;
auto issue_tma = [&](int iter_k, int stage_id) {
const int mbar_addr = tma_mbar_addr + stage_id * 8;
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B_smem = A_smem + A_size;
const int SFA_smem = B_smem + B_size;
const int SFB_smem = SFA_smem + SFA_size;
const int off_k = iter_k * BLOCK_K;
tma_3d_gmem2smem(A_smem, &A_tmap, 0, off_m, off_k / 256, mbar_addr, cache_A);
tma_3d_gmem2smem(B_smem, &B_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
const int rest_k = K / 16 / 4;
const char *SFA_src = SFA_ptr + ((off_m / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB_src = SFB_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
tma_gmem2smem(SFA_smem, SFA_src, SFA_size, mbar_addr, cache_A);
tma_gmem2smem(SFB_smem, SFB_src, SFB_size, mbar_addr, cache_B);
asm volatile(
"mbarrier.arrive.expect_tx.release.cta.shared::cta.b64 _, [%0], %1;"
:: "r"(mbar_addr), "r"(STAGE_SIZE)
: "memory"
);
};
constexpr int PRELOAD = (num_iters < NUM_STAGES) ? num_iters : NUM_STAGES;
for (int iter_k = 0; iter_k < PRELOAD; iter_k++) issue_tma(iter_k, iter_k);
for (int iter_k = NUM_STAGES; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int mma_phase = (iter_k / NUM_STAGES - 1) & 1;
mbarrier_wait(mma_mbar_addr + stage_id * 8, mma_phase);
issue_tma(iter_k, stage_id);
}
} else if (warp_id == NUM_WARPS - 1 && elect_sync()) {
constexpr int MMA_N = BLOCK_N;
constexpr int MMA_M = 128;
constexpr uint32_t i_desc = (1U << 7U) | (1U << 10U) | ((uint32_t)MMA_N >> 3U << 17U) | ((uint32_t)MMA_M >> 7U << 27U);
for (int iter_k = 0; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int tma_phase = (iter_k / NUM_STAGES) & 1;
mbarrier_wait(tma_mbar_addr + stage_id * 8, tma_phase);
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B_smem = A_smem + A_size;
const int SFA_smem = B_smem + B_size;
const int SFB_smem = SFA_smem + SFA_size;
auto make_desc_AB = [](int addr) -> uint64_t {
const int SBO = 8 * 128;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL) | (2ULL << 61ULL);
};
auto make_desc_SF = [](int addr) -> uint64_t {
const int SBO = 8 * 16;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL);
};
constexpr uint64_t SF_desc = make_desc_SF(0);
const uint64_t SFA_desc = SF_desc + ((uint64_t)SFA_smem >> 4ULL);
const uint64_t SFB_desc = SF_desc + ((uint64_t)SFB_smem >> 4ULL);
for (int k = 0; k < BLOCK_K / MMA_K; k++) {
uint64_t sfa_desc = SFA_desc + (uint64_t)k * (512ULL >> 4ULL);
uint64_t sfb_desc = SFB_desc + (uint64_t)k * (512ULL >> 4ULL);
tcgen05_cp_nvfp4(SFA_tmem + k * 4, sfa_desc);
tcgen05_cp_nvfp4(SFB_tmem + k * 4, sfb_desc);
}
for (int k1 = 0; k1 < BLOCK_K / 256; k1++)
for (int k2 = 0; k2 < 256 / MMA_K; k2++) {
uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);
uint64_t b_desc = make_desc_AB(B_smem + k1 * BLOCK_N * 128 + k2 * 32);
const int k_sf = k1 * 4 + k2;
const int scale_A_tmem = SFA_tmem + k_sf * 4;
const int scale_B_tmem = SFB_tmem + k_sf * 4 + (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);
const int enable_input_d = (k1 == 0 && k2 == 0) ? iter_k : 1;
tcgen05_mma_nvfp4(0, a_desc, b_desc, i_desc, scale_A_tmem, scale_B_tmem, enable_input_d);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mma_mbar_addr + stage_id * 8)
: "memory"
);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mainloop_mbar_addr)
: "memory"
);
} else if (tid < BLOCK_M) {
mbarrier_wait(mainloop_mbar_addr, 0);
asm volatile("tcgen05.fence::after_thread_sync;");
for (int mm = 0; mm < 2; mm++) {
float tmp[BLOCK_N / 2];
tcgen05_ld_16x256bx8(tmp, warp_id * 32 + mm * 16, 0);
if constexpr (BLOCK_N == 128) tcgen05_ld_16x256bx8(tmp + 32, warp_id * 32 + mm * 16, 64);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < BLOCK_N / 8; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + i * 8 + (lane_id & 3) * 2;
const float2 x0 = reinterpret_cast<const float2 *>(G1_ptr + (row + 0) * N + col)[0];
const float2 x8 = reinterpret_cast<const float2 *>(G1_ptr + (row + 8) * N + col)[0];
const float2 y0 = float2{tmp[i * 4 + 0], tmp[i * 4 + 1]};
const float2 y8 = float2{tmp[i * 4 + 2], tmp[i * 4 + 3]};
float2 o0;
float2 o8;
const float s00 = sigmoid_fast(x0.x);
const float s01 = sigmoid_fast(x0.y);
const float s80 = sigmoid_fast(x8.x);
const float s81 = sigmoid_fast(x8.y);
o0.x = (x0.x * s00) * y0.x;
o0.y = (x0.y * s01) * y0.y;
o8.x = (x8.x * s80) * y8.x;
o8.y = (x8.y * s81) * y8.y;
reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);
reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);
}
}
asm volatile("bar.sync 1, %0;" :: "r"(BLOCK_M) : "memory");
if (warp_id == 0) asm volatile("tcgen05.dealloc.cta_group::1.sync.aligned.b32 %0, %1;" :: "r"(0), "r"(BLOCK_N * 2));
}
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
__global__ __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)
void dual_gemm_silu_mul_kernel(
const __grid_constant__ CUtensorMap A_tmap,
const __grid_constant__ CUtensorMap B1_tmap,
const __grid_constant__ CUtensorMap B2_tmap,
const char *SFA_ptr,
const char *SFB1_ptr,
const char *SFB2_ptr,
half *Out_ptr,
int M, int N
) {
const int tid = threadIdx.x;
const int lane_id = tid & 31;
const int warp_id = tid >> 5;
const int bid_m = (int)blockIdx.y;
const int bid_n = (int)blockIdx.x;
const int off_m = bid_m * BLOCK_M;
const int off_n = bid_n * BLOCK_N;
constexpr int NUM_WARPS = BLOCK_M / WARP_SIZE + 2;
extern __shared__ __align__(1024) char smem_ptr[];
const int smem = static_cast<int>(__cvta_generic_to_shared(smem_ptr));
constexpr int A_size = BLOCK_M * BLOCK_K / 2;
constexpr int B_size = BLOCK_N * BLOCK_K / 2;
constexpr int SFA_size = 128 * BLOCK_K / 16;
constexpr int SFB_size = 128 * BLOCK_K / 16;
constexpr int STAGE_SIZE = A_size + (2 * B_size) + SFA_size + (2 * SFB_size);
#pragma nv_diag_suppress static_var_with_dynamic_init
__shared__ int64_t mbars[NUM_STAGES * 2 + 1];
const int tma_mbar_addr = static_cast<int>(__cvta_generic_to_shared(mbars));
const int mma_mbar_addr = tma_mbar_addr + NUM_STAGES * 8;
const int mainloop_mbar_addr = mma_mbar_addr + NUM_STAGES * 8;
constexpr int OUT1_tmem = 0;
constexpr int OUT2_tmem = BLOCK_N;
constexpr int SFA_tmem = 2 * BLOCK_N;
constexpr int SFB1_tmem = SFA_tmem + 4 * (BLOCK_K / MMA_K);
constexpr int SFB2_tmem = SFB1_tmem + 4 * (BLOCK_K / MMA_K);
constexpr int TMEM_ALLOC = (BLOCK_N == 128) ? 512 : (BLOCK_N * 4);
if (warp_id == 0 && elect_sync()) {
for (int i = 0; i < NUM_STAGES * 2 + 1; i++) mbarrier_init(tma_mbar_addr + i * 8, 1);
asm volatile("fence.mbarrier_init.release.cluster;");
} else if (warp_id == 1) {
asm volatile(
"tcgen05.alloc.cta_group::1.sync.aligned.shared::cta.b32 [%0], %1;"
:: "r"(smem), "r"(TMEM_ALLOC)
);
}
__syncthreads();
constexpr int num_iters = K / BLOCK_K;
if (warp_id == NUM_WARPS - 2 && elect_sync()) {
const uint64_t cache_A = EVICT_FIRST;
const uint64_t cache_B = EVICT_FIRST;
auto issue_tma = [&](int iter_k, int stage_id) {
const int mbar_addr = tma_mbar_addr + stage_id * 8;
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B1_smem = A_smem + A_size;
const int B2_smem = B1_smem + B_size;
const int SFA_smem = B2_smem + B_size;
const int SFB1_smem = SFA_smem + SFA_size;
const int SFB2_smem = SFB1_smem + SFB_size;
const int off_k = iter_k * BLOCK_K;
tma_3d_gmem2smem(A_smem, &A_tmap, 0, off_m, off_k / 256, mbar_addr, cache_A);
tma_3d_gmem2smem(B1_smem, &B1_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
tma_3d_gmem2smem(B2_smem, &B2_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
const int rest_k = K / 16 / 4;
const char *SFA_src = SFA_ptr + ((off_m / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB1_src = SFB1_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB2_src = SFB2_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
tma_gmem2smem(SFA_smem, SFA_src, SFA_size, mbar_addr, cache_A);
tma_gmem2smem(SFB1_smem, SFB1_src, SFB_size, mbar_addr, cache_B);
tma_gmem2smem(SFB2_smem, SFB2_src, SFB_size, mbar_addr, cache_B);
asm volatile(
"mbarrier.arrive.expect_tx.release.cta.shared::cta.b64 _, [%0], %1;"
:: "r"(mbar_addr), "r"(STAGE_SIZE)
: "memory"
);
};
constexpr int PRELOAD = (num_iters < NUM_STAGES) ? num_iters : NUM_STAGES;
for (int iter_k = 0; iter_k < PRELOAD; iter_k++) issue_tma(iter_k, iter_k);
for (int iter_k = NUM_STAGES; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int mma_phase = (iter_k / NUM_STAGES - 1) & 1;
mbarrier_wait(mma_mbar_addr + stage_id * 8, mma_phase);
issue_tma(iter_k, stage_id);
}
} else if (warp_id == NUM_WARPS - 1 && elect_sync()) {
constexpr int MMA_N = BLOCK_N;
constexpr int MMA_M = 128;
constexpr uint32_t i_desc = (1U << 7U) | (1U << 10U) | ((uint32_t)MMA_N >> 3U << 17U) | ((uint32_t)MMA_M >> 7U << 27U);
for (int iter_k = 0; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int tma_phase = (iter_k / NUM_STAGES) & 1;
mbarrier_wait(tma_mbar_addr + stage_id * 8, tma_phase);
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B1_smem = A_smem + A_size;
const int B2_smem = B1_smem + B_size;
const int SFA_smem = B2_smem + B_size;
const int SFB1_smem = SFA_smem + SFA_size;
const int SFB2_smem = SFB1_smem + SFB_size;
auto make_desc_AB = [](int addr) -> uint64_t {
const int SBO = 8 * 128;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL) | (2ULL << 61ULL);
};
auto make_desc_SF = [](int addr) -> uint64_t {
const int SBO = 8 * 16;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL);
};
constexpr uint64_t SF_desc = make_desc_SF(0);
const uint64_t SFA_desc = SF_desc + ((uint64_t)SFA_smem >> 4ULL);
const uint64_t SFB1_desc = SF_desc + ((uint64_t)SFB1_smem >> 4ULL);
const uint64_t SFB2_desc = SF_desc + ((uint64_t)SFB2_smem >> 4ULL);
#pragma unroll
for (int k = 0; k < BLOCK_K / MMA_K; k++) {
const uint64_t sfa_desc = SFA_desc + (uint64_t)k * (512ULL >> 4ULL);
const uint64_t sfb1_desc = SFB1_desc + (uint64_t)k * (512ULL >> 4ULL);
const uint64_t sfb2_desc = SFB2_desc + (uint64_t)k * (512ULL >> 4ULL);
tcgen05_cp_nvfp4(SFA_tmem + k * 4, sfa_desc);
tcgen05_cp_nvfp4(SFB1_tmem + k * 4, sfb1_desc);
tcgen05_cp_nvfp4(SFB2_tmem + k * 4, sfb2_desc);
}
const int sel_n = (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);
#pragma unroll
for (int k1 = 0; k1 < BLOCK_K / 256; k1++) {
#pragma unroll
for (int k2 = 0; k2 < 256 / MMA_K; k2++) {
const uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);
const uint64_t b1_desc = make_desc_AB(B1_smem + k1 * BLOCK_N * 128 + k2 * 32);
const uint64_t b2_desc = make_desc_AB(B2_smem + k1 * BLOCK_N * 128 + k2 * 32);
const int k_sf = k1 * 4 + k2;
const int scale_A_tmem = SFA_tmem + k_sf * 4;
const int scale_B1_tmem = SFB1_tmem + k_sf * 4 + sel_n;
const int scale_B2_tmem = SFB2_tmem + k_sf * 4 + sel_n;
const int enable_input_d = (k1 == 0 && k2 == 0) ? iter_k : 1;
tcgen05_mma_nvfp4(OUT1_tmem, a_desc, b1_desc, i_desc, scale_A_tmem, scale_B1_tmem, enable_input_d);
tcgen05_mma_nvfp4(OUT2_tmem, a_desc, b2_desc, i_desc, scale_A_tmem, scale_B2_tmem, enable_input_d);
}
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mma_mbar_addr + stage_id * 8)
: "memory"
);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mainloop_mbar_addr)
: "memory"
);
} else if (tid < BLOCK_M) {
mbarrier_wait(mainloop_mbar_addr, 0);
asm volatile("tcgen05.fence::after_thread_sync;");
constexpr int HALF_ITERS = 8;
for (int mm = 0; mm < 2; mm++) {
{
float x[32];
float y[32];
tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 0);
tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < HALF_ITERS; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + i * 8 + (lane_id & 3) * 2;
const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};
const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};
const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};
const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};
float2 o0;
float2 o8;
const float s00 = sigmoid_fast(x0.x);
const float s01 = sigmoid_fast(x0.y);
const float s80 = sigmoid_fast(x8.x);
const float s81 = sigmoid_fast(x8.y);
o0.x = (x0.x * s00) * y0.x;
o0.y = (x0.y * s01) * y0.y;
o8.x = (x8.x * s80) * y8.x;
o8.y = (x8.y * s81) * y8.y;
reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);
reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);
}
}
if constexpr (BLOCK_N == 128) {
float x[32];
float y[32];
tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 64);
tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem + 64);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < HALF_ITERS; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + 64 + i * 8 + (lane_id & 3) * 2;
const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};
const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};
const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};
const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};
float2 o0;
float2 o8;
const float s00 = sigmoid_fast(x0.x);
const float s01 = sigmoid_fast(x0.y);
const float s80 = sigmoid_fast(x8.x);
const float s81 = sigmoid_fast(x8.y);
o0.x = (x0.x * s00) * y0.x;
o0.y = (x0.y * s01) * y0.y;
o8.x = (x8.x * s80) * y8.x;
o8.y = (x8.y * s81) * y8.y;
reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);
reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);
}
}
}
asm volatile("bar.sync 1, %0;" :: "r"(BLOCK_M) : "memory");
if (warp_id == 0) asm volatile("tcgen05.dealloc.cta_group::1.sync.aligned.b32 %0, %1;" :: "r"(0), "r"(TMEM_ALLOC));
}
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
__global__ __cluster_dims__(2, 1, 1) __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)
void dual_gemm_silu_mul_cluster_kernel(
const __grid_constant__ CUtensorMap A_tmap,
const __grid_constant__ CUtensorMap B1_tmap,
const __grid_constant__ CUtensorMap B2_tmap,
const char *SFA_ptr,
const char *SFB1_ptr,
const char *SFB2_ptr,
half *Out_ptr,
int M, int N
) {
const int tid = threadIdx.x;
const int lane_id = tid & 31;
const int warp_id = tid >> 5;
const int bid_m = (int)blockIdx.y;
const int bid_n = (int)blockIdx.x;
const int off_m = bid_m * BLOCK_M;
const int off_n = bid_n * BLOCK_N;
constexpr int NUM_WARPS = BLOCK_M / WARP_SIZE + 2;
extern __shared__ __align__(1024) char smem_ptr[];
const int smem = static_cast<int>(__cvta_generic_to_shared(smem_ptr));
constexpr int A_size = BLOCK_M * BLOCK_K / 2;
constexpr int B_size = BLOCK_N * BLOCK_K / 2;
constexpr int SFA_size = 128 * BLOCK_K / 16;
constexpr int SFB_size = 128 * BLOCK_K / 16;
constexpr int STAGE_SIZE = A_size + (2 * B_size) + SFA_size + (2 * SFB_size);
#pragma nv_diag_suppress static_var_with_dynamic_init
__shared__ int64_t mbars[NUM_STAGES * 2 + 1];
const int tma_mbar_addr = static_cast<int>(__cvta_generic_to_shared(mbars));
const int mma_mbar_addr = tma_mbar_addr + NUM_STAGES * 8;
const int mainloop_mbar_addr = mma_mbar_addr + NUM_STAGES * 8;
constexpr int OUT1_tmem = 0;
constexpr int OUT2_tmem = BLOCK_N;
constexpr int SFA_tmem = 2 * BLOCK_N;
constexpr int SFB1_tmem = SFA_tmem + 4 * (BLOCK_K / MMA_K);
constexpr int SFB2_tmem = SFB1_tmem + 4 * (BLOCK_K / MMA_K);
constexpr int TMEM_ALLOC = (BLOCK_N == 128) ? 512 : (BLOCK_N * 4);
if (warp_id == 0 && elect_sync()) {
for (int i = 0; i < NUM_STAGES * 2 + 1; i++) mbarrier_init(tma_mbar_addr + i * 8, 1);
asm volatile("fence.mbarrier_init.release.cluster;");
} else if (warp_id == 1) {
asm volatile(
"tcgen05.alloc.cta_group::1.sync.aligned.shared::cta.b32 [%0], %1;"
:: "r"(smem), "r"(TMEM_ALLOC)
);
}
__syncthreads();
constexpr int num_iters = K / BLOCK_K;
if (warp_id == NUM_WARPS - 2 && elect_sync()) {
const uint64_t cache_A = EVICT_FIRST;
const uint64_t cache_B = EVICT_FIRST;
auto issue_tma = [&](int iter_k, int stage_id) {
const int mbar_addr = tma_mbar_addr + stage_id * 8;
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B1_smem = A_smem + A_size;
const int B2_smem = B1_smem + B_size;
const int SFA_smem = B2_smem + B_size;
const int SFB1_smem = SFA_smem + SFA_size;
const int SFB2_smem = SFB1_smem + SFB_size;
const int off_k = iter_k * BLOCK_K;
tma_3d_gmem2smem_cluster2(A_smem, &A_tmap, 0, off_m, off_k / 256, mbar_addr, cache_A);
tma_3d_gmem2smem(B1_smem, &B1_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
tma_3d_gmem2smem(B2_smem, &B2_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);
const int rest_k = K / 16 / 4;
const char *SFA_src = SFA_ptr + ((off_m / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB1_src = SFB1_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
const char *SFB2_src = SFB2_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;
tma_gmem2smem(SFA_smem, SFA_src, SFA_size, mbar_addr, cache_A);
tma_gmem2smem(SFB1_smem, SFB1_src, SFB_size, mbar_addr, cache_B);
tma_gmem2smem(SFB2_smem, SFB2_src, SFB_size, mbar_addr, cache_B);
asm volatile(
"mbarrier.arrive.expect_tx.release.cta.shared::cta.b64 _, [%0], %1;"
:: "r"(mbar_addr), "r"(STAGE_SIZE)
: "memory"
);
};
constexpr int PRELOAD = (num_iters < NUM_STAGES) ? num_iters : NUM_STAGES;
for (int iter_k = 0; iter_k < PRELOAD; iter_k++) issue_tma(iter_k, iter_k);
for (int iter_k = NUM_STAGES; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int mma_phase = (iter_k / NUM_STAGES - 1) & 1;
mbarrier_wait(mma_mbar_addr + stage_id * 8, mma_phase);
issue_tma(iter_k, stage_id);
}
} else if (warp_id == NUM_WARPS - 1 && elect_sync()) {
constexpr int MMA_N = BLOCK_N;
constexpr int MMA_M = 128;
constexpr uint32_t i_desc = (1U << 7U) | (1U << 10U) | ((uint32_t)MMA_N >> 3U << 17U) | ((uint32_t)MMA_M >> 7U << 27U);
for (int iter_k = 0; iter_k < num_iters; iter_k++) {
const int stage_id = iter_k % NUM_STAGES;
const int tma_phase = (iter_k / NUM_STAGES) & 1;
mbarrier_wait(tma_mbar_addr + stage_id * 8, tma_phase);
const int A_smem = smem + stage_id * STAGE_SIZE;
const int B1_smem = A_smem + A_size;
const int B2_smem = B1_smem + B_size;
const int SFA_smem = B2_smem + B_size;
const int SFB1_smem = SFA_smem + SFA_size;
const int SFB2_smem = SFB1_smem + SFB_size;
auto make_desc_AB = [](int addr) -> uint64_t {
const int SBO = 8 * 128;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL) | (2ULL << 61ULL);
};
auto make_desc_SF = [](int addr) -> uint64_t {
const int SBO = 8 * 16;
return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL);
};
constexpr uint64_t SF_desc = make_desc_SF(0);
const uint64_t SFA_desc = SF_desc + ((uint64_t)SFA_smem >> 4ULL);
const uint64_t SFB1_desc = SF_desc + ((uint64_t)SFB1_smem >> 4ULL);
const uint64_t SFB2_desc = SF_desc + ((uint64_t)SFB2_smem >> 4ULL);
#pragma unroll
for (int k = 0; k < BLOCK_K / MMA_K; k++) {
const uint64_t sfa_desc = SFA_desc + (uint64_t)k * (512ULL >> 4ULL);
const uint64_t sfb1_desc = SFB1_desc + (uint64_t)k * (512ULL >> 4ULL);
const uint64_t sfb2_desc = SFB2_desc + (uint64_t)k * (512ULL >> 4ULL);
tcgen05_cp_nvfp4(SFA_tmem + k * 4, sfa_desc);
tcgen05_cp_nvfp4(SFB1_tmem + k * 4, sfb1_desc);
tcgen05_cp_nvfp4(SFB2_tmem + k * 4, sfb2_desc);
}
const int sel_n = (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);
#pragma unroll
for (int k1 = 0; k1 < BLOCK_K / 256; k1++) {
#pragma unroll
for (int k2 = 0; k2 < 256 / MMA_K; k2++) {
const uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);
const uint64_t b1_desc = make_desc_AB(B1_smem + k1 * BLOCK_N * 128 + k2 * 32);
const uint64_t b2_desc = make_desc_AB(B2_smem + k1 * BLOCK_N * 128 + k2 * 32);
const int k_sf = k1 * 4 + k2;
const int scale_A_tmem = SFA_tmem + k_sf * 4;
const int scale_B1_tmem = SFB1_tmem + k_sf * 4 + sel_n;
const int scale_B2_tmem = SFB2_tmem + k_sf * 4 + sel_n;
const int enable_input_d = (k1 == 0 && k2 == 0) ? iter_k : 1;
tcgen05_mma_nvfp4(OUT1_tmem, a_desc, b1_desc, i_desc, scale_A_tmem, scale_B1_tmem, enable_input_d);
tcgen05_mma_nvfp4(OUT2_tmem, a_desc, b2_desc, i_desc, scale_A_tmem, scale_B2_tmem, enable_input_d);
}
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mma_mbar_addr + stage_id * 8)
: "memory"
);
}
asm volatile(
"tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"
:: "r"(mainloop_mbar_addr)
: "memory"
);
} else if (tid < BLOCK_M) {
mbarrier_wait(mainloop_mbar_addr, 0);
asm volatile("tcgen05.fence::after_thread_sync;");
constexpr int HALF_ITERS = 8;
for (int mm = 0; mm < 2; mm++) {
{
float x[32];
float y[32];
tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 0);
tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < HALF_ITERS; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + i * 8 + (lane_id & 3) * 2;
const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};
const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};
const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};
const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};
float2 o0;
float2 o8;
const float s00 = sigmoid_fast(x0.x);
const float s01 = sigmoid_fast(x0.y);
const float s80 = sigmoid_fast(x8.x);
const float s81 = sigmoid_fast(x8.y);
o0.x = (x0.x * s00) * y0.x;
o0.y = (x0.y * s01) * y0.y;
o8.x = (x8.x * s80) * y8.x;
o8.y = (x8.y * s81) * y8.y;
reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);
reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);
}
}
if constexpr (BLOCK_N == 128) {
float x[32];
float y[32];
tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 64);
tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem + 64);
asm volatile("tcgen05.wait::ld.sync.aligned;");
#pragma unroll
for (int i = 0; i < HALF_ITERS; i++) {
const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;
const int col = off_n + 64 + i * 8 + (lane_id & 3) * 2;
const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};
const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};
const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};
const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};
float2 o0;
float2 o8;
const float s00 = sigmoid_fast(x0.x);
const float s01 = sigmoid_fast(x0.y);
const float s80 = sigmoid_fast(x8.x);
const float s81 = sigmoid_fast(x8.y);
o0.x = (x0.x * s00) * y0.x;
o0.y = (x0.y * s01) * y0.y;
o8.x = (x8.x * s80) * y8.x;
o8.y = (x8.y * s81) * y8.y;
reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);
reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);
}
}
}
asm volatile("bar.sync 1, %0;" :: "r"(BLOCK_M) : "memory");
if (warp_id == 0) asm volatile("tcgen05.dealloc.cta_group::1.sync.aligned.b32 %0, %1;" :: "r"(0), "r"(TMEM_ALLOC));
}
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
static inline void launch_gemm_f32(
const at::Tensor& A,
const at::Tensor& B,
const at::Tensor& SFA,
const at::Tensor& SFB,
at::Tensor& C
) {
const int M = (int)A.size(0);
const int N = (int)B.size(0);
auto A_ptr = reinterpret_cast<const char *>(A.data_ptr());
auto B_ptr = reinterpret_cast<const char *>(B.data_ptr());
auto SFA_ptr = reinterpret_cast<const char *>(SFA.data_ptr());
auto SFB_ptr = reinterpret_cast<const char *>(SFB.data_ptr());
auto C_ptr = reinterpret_cast<float *>(C.data_ptr());
static TmapCache cache_A;
static TmapCache cache_B;
const CUtensorMap A_tmap = cache_A.get(A_ptr, (uint64_t)M, (uint64_t)K, (uint32_t)BLOCK_M, (uint32_t)BLOCK_K);
const CUtensorMap B_tmap = cache_B.get(B_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);
dim3 grid(1, (unsigned)((M / BLOCK_M) * (N / BLOCK_N)));
constexpr int tb_size = BLOCK_M + 2 * WARP_SIZE;
constexpr int AB_size = (BLOCK_M + BLOCK_N) * (BLOCK_K / 2);
constexpr int SFAB_size = 128 * (BLOCK_K / 16) * 2;
constexpr int smem_size = (AB_size + SFAB_size) * NUM_STAGES;
auto kptr = gemm_f32_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;
static bool attr_set = false;
if (!attr_set) {
if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);
attr_set = true;
}
kptr<<<grid, tb_size, smem_size>>>(A_tmap, B_tmap, SFA_ptr, SFB_ptr, C_ptr, M, N);
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
static inline void launch_gemm_silu_mul(
const at::Tensor& A,
const at::Tensor& B,
const at::Tensor& SFA,
const at::Tensor& SFB,
const at::Tensor& g1,
at::Tensor& out
) {
const int M = (int)A.size(0);
const int N = (int)B.size(0);
auto A_ptr = reinterpret_cast<const char *>(A.data_ptr());
auto B_ptr = reinterpret_cast<const char *>(B.data_ptr());
auto SFA_ptr = reinterpret_cast<const char *>(SFA.data_ptr());
auto SFB_ptr = reinterpret_cast<const char *>(SFB.data_ptr());
auto G1_ptr = reinterpret_cast<const float *>(g1.data_ptr());
auto Out_ptr = reinterpret_cast<half *>(out.data_ptr());
static TmapCache cache_A;
static TmapCache cache_B;
const CUtensorMap A_tmap = cache_A.get(A_ptr, (uint64_t)M, (uint64_t)K, (uint32_t)BLOCK_M, (uint32_t)BLOCK_K);
const CUtensorMap B_tmap = cache_B.get(B_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);
dim3 grid(1, (unsigned)((M / BLOCK_M) * (N / BLOCK_N)));
constexpr int tb_size = BLOCK_M + 2 * WARP_SIZE;
constexpr int AB_size = (BLOCK_M + BLOCK_N) * (BLOCK_K / 2);
constexpr int SFAB_size = 128 * (BLOCK_K / 16) * 2;
constexpr int smem_size = (AB_size + SFAB_size) * NUM_STAGES;
auto kptr = gemm_silu_mul_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;
static bool attr_set = false;
if (!attr_set) {
if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);
attr_set = true;
}
kptr<<<grid, tb_size, smem_size>>>(A_tmap, B_tmap, SFA_ptr, SFB_ptr, G1_ptr, Out_ptr, M, N);
}
template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>
static inline void launch_dual_gemm_silu_mul(
const at::Tensor& A,
const at::Tensor& B1,
const at::Tensor& B2,
const at::Tensor& SFA,
const at::Tensor& SFB1,
const at::Tensor& SFB2,
at::Tensor& out
) {
const int M = (int)A.size(0);
const int N = (int)B1.size(0);
auto A_ptr = reinterpret_cast<const char *>(A.data_ptr());
auto B1_ptr = reinterpret_cast<const char *>(B1.data_ptr());
auto B2_ptr = reinterpret_cast<const char *>(B2.data_ptr());
auto SFA_ptr = reinterpret_cast<const char *>(SFA.data_ptr());
auto SFB1_ptr = reinterpret_cast<const char *>(SFB1.data_ptr());
auto SFB2_ptr = reinterpret_cast<const char *>(SFB2.data_ptr());
auto Out_ptr = reinterpret_cast<half *>(out.data_ptr());
static TmapCache cache_A;
static TmapCache cache_B1;
static TmapCache cache_B2;
const CUtensorMap A_tmap = cache_A.get(A_ptr, (uint64_t)M, (uint64_t)K, (uint32_t)BLOCK_M, (uint32_t)BLOCK_K);
const CUtensorMap B1_tmap = cache_B1.get(B1_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);
const CUtensorMap B2_tmap = cache_B2.get(B2_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);
const int grid_x = N / BLOCK_N;
const int grid_y = M / BLOCK_M;
dim3 grid((unsigned)grid_x, (unsigned)grid_y);
constexpr int tb_size = BLOCK_M + 2 * WARP_SIZE;
constexpr int AB_size = (BLOCK_M + 2 * BLOCK_N) * (BLOCK_K / 2);
constexpr int SF_size = 128 * (BLOCK_K / 16) * 3;
constexpr int smem_size = (AB_size + SF_size) * NUM_STAGES;
if ((grid_x & 1) == 0) {
auto kptr = dual_gemm_silu_mul_cluster_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;
static bool attr_set = false;
if (!attr_set) {
if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);
cudaFuncSetAttribute(kptr, cudaFuncAttributeNonPortableClusterSizeAllowed, 1);
attr_set = true;
}
kptr<<<grid, tb_size, smem_size>>>(A_tmap, B1_tmap, B2_tmap, SFA_ptr, SFB1_ptr, SFB2_ptr, Out_ptr, M, N);
} else {
auto kptr = dual_gemm_silu_mul_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;
static bool attr_set = false;
if (!attr_set) {
if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);
attr_set = true;
}
kptr<<<grid, tb_size, smem_size>>>(A_tmap, B1_tmap, B2_tmap, SFA_ptr, SFB1_ptr, SFB2_ptr, Out_ptr, M, N);
}
}
__global__ void silu_mul_f32_vec2(const float* __restrict__ x, const float* __restrict__ y, half* __restrict__ out, int64_t n2) {
const int64_t idx = int64_t(blockIdx.x) * blockDim.x + threadIdx.x;
if (idx >= n2) return;
const float2 fx = reinterpret_cast<const float2*>(x)[idx];
const float2 fy = reinterpret_cast<const float2*>(y)[idx];
float2 o;
const float sx0 = sigmoid_fast(fx.x);
const float sx1 = sigmoid_fast(fx.y);
o.x = (fx.x * sx0) * fy.x;
o.y = (fx.y * sx1) * fy.y;
reinterpret_cast<half2*>(out)[idx] = __float22half2_rn(o);
}
static inline void launch_silu_mul_f32(const at::Tensor& g1, const at::Tensor& g2, at::Tensor& out) {
const int64_t n = out.numel();
TORCH_CHECK((n & 1) == 0, "n");
const int64_t n2 = n >> 1;
const int threads = 256;
const int blocks = (int)((n2 + threads - 1) / threads);
silu_mul_f32_vec2<<<blocks, threads>>>(
reinterpret_cast<const float*>(g1.data_ptr()),
reinterpret_cast<const float*>(g2.data_ptr()),
reinterpret_cast<half*>(out.data_ptr()),
n2
);
}
at::Tensor fused(
const at::Tensor& A,
const at::Tensor& B1,
const at::Tensor& B2,
const at::Tensor& SFA,
const at::Tensor& SFB1,
const at::Tensor& SFB2,
at::Tensor& out,
at::Tensor& g1,
at::Tensor& g2
) {
TORCH_CHECK(A.is_cuda() && B1.is_cuda() && B2.is_cuda(), "cuda");
TORCH_CHECK(SFA.is_cuda() && SFB1.is_cuda() && SFB2.is_cuda(), "cuda");
TORCH_CHECK(out.is_cuda() && g1.is_cuda() && g2.is_cuda(), "cuda");
TORCH_CHECK(A.dim() == 3 && B1.dim() == 3 && B2.dim() == 3, "dim");
TORCH_CHECK(out.dim() == 3 && g1.dim() == 3 && g2.dim() == 3, "dim");
const int64_t M = A.size(0);
const int64_t Kp = A.size(1);
const int64_t L = A.size(2);
const int64_t N = B1.size(0);
TORCH_CHECK(L == 1, "l");
TORCH_CHECK(B1.size(1) == Kp && B1.size(2) == L, "b1");
TORCH_CHECK(B2.size(1) == Kp && B2.size(2) == L, "b2");
TORCH_CHECK(out.size(0) == M && out.size(1) == N && out.size(2) == L, "out");
TORCH_CHECK(g1.size(0) == M && g1.size(1) == N && g1.size(2) == L, "g1");
TORCH_CHECK(g2.size(0) == M && g2.size(1) == N && g2.size(2) == L, "g2");
TORCH_CHECK((M % 128) == 0, "m");
TORCH_CHECK((N % 64) == 0, "n");
const int K = (int)(Kp * 2);
const bool use_dual = ((N & 127) == 0);
const bool use_128n = use_dual && (M >= 512);
const bool use_small_m = (M == 256);
if (K == 7168) {
if (use_dual) {
if (use_small_m) {
launch_dual_gemm_silu_mul<7168, 128, 64, 256, 4>(A, B1, B2, SFA, SFB1, SFB2, out);
} else {
launch_dual_gemm_silu_mul<7168, 128, 128, 256, 4>(A, B1, B2, SFA, SFB1, SFB2, out);
}
} else {
launch_gemm_f32<7168, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<7168, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 4096) {
if (use_dual) {
if (use_small_m) {
launch_dual_gemm_silu_mul<4096, 128, 64, 256, 4>(A, B1, B2, SFA, SFB1, SFB2, out);
} else {
launch_dual_gemm_silu_mul<4096, 128, 128, 256, 4>(A, B1, B2, SFA, SFB1, SFB2, out);
}
} else {
launch_gemm_f32<4096, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<4096, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 2304) {
if (use_128n) {
launch_gemm_f32<2304, 128, 128, 256, 6>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<2304, 128, 128, 256, 6>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
} else {
launch_gemm_f32<2304, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<2304, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 2048) {
if (use_128n) {
launch_gemm_f32<2048, 128, 128, 512, 3>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<2048, 128, 128, 512, 3>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
} else {
launch_gemm_f32<2048, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<2048, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 1536) {
if (use_128n) {
launch_gemm_f32<1536, 128, 128, 512, 3>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<1536, 128, 128, 512, 3>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
} else {
launch_gemm_f32<1536, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<1536, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 512) {
if (use_128n) {
launch_gemm_f32<512, 128, 128, 512, 1>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<512, 128, 128, 512, 1>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
} else {
launch_gemm_f32<512, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<512, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else if (K == 256) {
if (use_128n) {
launch_gemm_f32<256, 128, 128, 256, 1>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<256, 128, 128, 256, 1>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
} else {
launch_gemm_f32<256, 128, 64, 256, 8>(A, B1, SFA, SFB1, g1);
launch_gemm_f32<256, 128, 64, 256, 8>(A, B2, SFA, SFB2, g2);
launch_silu_mul_f32(g1, g2, out);
}
} else {
TORCH_CHECK(false, "k ", K);
}
return out;
}
TORCH_LIBRARY(nvfp4_dual_lib, m) {
m.def("fused(Tensor A, Tensor B1, Tensor B2, Tensor SFA, Tensor SFB1, Tensor SFB2, Tensor(a!) out, Tensor(b!) g1, Tensor(c!) g2) -> Tensor");
m.impl("fused", &fused);
}
"""
_loaded = False
def _load():
global _loaded
if _loaded:
return
load_inline(
name="nvfp4_dual_ext_tc_dual_fused_final",
cpp_sources="",
cuda_sources=_CUDA_SRC,
functions=None,
with_cuda=True,
extra_cuda_cflags=[
"-O3",
"-gencode=arch=compute_100a,code=sm_100a",
"--use_fast_math",
"--expt-relaxed-constexpr",
"--relocatable-device-code=false",
],
extra_ldflags=["-lcuda"],
verbose=False,
is_python_module=False,
no_implicit_headers=True,
)
_loaded = True
_buf_cache = {}
def _get_buf(tag, shape, device):
key = (tag, shape, device)
t = _buf_cache.get(key)
if t is None or t.shape != shape or t.device != device:
t = torch.empty(shape, device=device, dtype=torch.float32)
_buf_cache[key] = t
return t
def custom_kernel(data):
_load()
a, b1, b2, _sfa, _sfb1, _sfb2, sfa_p, sfb1_p, sfb2_p, c = data
g1 = _get_buf(1, c.shape, a.device)
g2 = _get_buf(2, c.shape, a.device)
return torch.ops.nvfp4_dual_lib.fused(a, b1, b2, sfa_p, sfb1_p, sfb2_p, c, g1, g2)
__all__ = ["custom_kernel"]
scrolls · 1397 lines total
Source code from GPU Mode and the KernelBot dataset · June 9 Researcher Reciprocity License v1.0
Changes from previous submission
Against this author's previous submission submission 251425.
⋯ 18 unchanged linesconstexpr uint64_t EVICT_FIRST = 0x12F0000000000000ULL;constexpr uint64_t EVICT_LAST = 0x14F0000000000000ULL;+ constexpr uint32_t PEER_MASK = 0xFEFFFFFFU;__device__ __forceinline__ constexpr uint64_t desc_encode(uint64_t x) { return (x & 0x3'FFFFULL) >> 4ULL; }⋯ 47 unchanged lines);}+ __device__ __forceinline__ void tma_3d_gmem2smem_cluster2(int dst, const void *tmap_ptr, int x, int y, int z, int mbar_addr, uint64_t cache_policy) {+ asm volatile(+ "cp.async.bulk.tensor.3d.cta_group::2.shared::cluster.global.mbarrier::complete_tx::bytes.L2::cache_hint "+ "[%0], [%1, {%2, %3, %4}], [%5], %6;"+ :: "r"(dst), "l"(tmap_ptr), "r"(x), "r"(y), "r"(z), "r"(mbar_addr), "l"(cache_policy)+ : "memory"+ );+ }+__device__ __forceinline__ void tcgen05_cp_nvfp4(int taddr, uint64_t s_desc) {asm volatile("tcgen05.cp.cta_group::1.32x128b.warpx4 [%0], %1;" :: "r"(taddr), "l"(s_desc));}⋯ 41 unchanged linestcgen05_ld_32regs<SHAPE::_16x256b, NUM::x8>(tmp, row, col);}+ __device__ __forceinline__ float exp2_approx(float x) {+ float y;+ asm("ex2.approx.f32 %0, %1;" : "=f"(y) : "f"(x));+ return y;+ }++ __device__ __forceinline__ float sigmoid_fast(float x) {+ const float t = exp2_approx(-x * 1.4426950408889634f);+ return __fdividef(1.0f, 1.0f + t);+ }+static inline void ck_cu(CUresult err) {if (err == CUDA_SUCCESS) return;const char *msg = nullptr;⋯ 394 unchanged linesfloat2 o0;float2 o8;- const float s00 = 1.0f / (1.0f + __expf(-x0.x));- const float s01 = 1.0f / (1.0f + __expf(-x0.y));- const float s80 = 1.0f / (1.0f + __expf(-x8.x));- const float s81 = 1.0f / (1.0f + __expf(-x8.y));+ const float s00 = sigmoid_fast(x0.x);+ const float s01 = sigmoid_fast(x0.y);+ const float s80 = sigmoid_fast(x8.x);+ const float s81 = sigmoid_fast(x8.y);o0.x = (x0.x * s00) * y0.x;o0.y = (x0.y * s01) * y0.y;o8.x = (x8.x * s80) * y8.x;⋯ 22 unchanged linesint M, int N) {const int tid = threadIdx.x;- const int bid = blockIdx.y;const int lane_id = tid & 31;const int warp_id = tid >> 5;- const int grid_n = N / BLOCK_N;- const int bid_m = bid / grid_n;- const int bid_n = bid - bid_m * grid_n;+ const int bid_m = (int)blockIdx.y;+ const int bid_n = (int)blockIdx.x;const int off_m = bid_m * BLOCK_M;const int off_n = bid_n * BLOCK_N;⋯ 116 unchanged linestcgen05_cp_nvfp4(SFB2_tmem + k * 4, sfb2_desc);}- for (int k1 = 0; k1 < BLOCK_K / 256; k1++)+ const int sel_n = (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);++ #pragma unroll+ for (int k1 = 0; k1 < BLOCK_K / 256; k1++) {+ #pragma unrollfor (int k2 = 0; k2 < 256 / MMA_K; k2++) {const uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);const uint64_t b1_desc = make_desc_AB(B1_smem + k1 * BLOCK_N * 128 + k2 * 32);⋯ 1 unchanged linesconst int k_sf = k1 * 4 + k2;const int scale_A_tmem = SFA_tmem + k_sf * 4;- const int sel_n = (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);const int scale_B1_tmem = SFB1_tmem + k_sf * 4 + sel_n;const int scale_B2_tmem = SFB2_tmem + k_sf * 4 + sel_n;⋯ 1 unchanged linestcgen05_mma_nvfp4(OUT1_tmem, a_desc, b1_desc, i_desc, scale_A_tmem, scale_B1_tmem, enable_input_d);tcgen05_mma_nvfp4(OUT2_tmem, a_desc, b2_desc, i_desc, scale_A_tmem, scale_B2_tmem, enable_input_d);}+ }asm volatile("tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"⋯ 32 unchanged linesfloat2 o0;float2 o8;- const float s00 = 1.0f / (1.0f + __expf(-x0.x));- const float s01 = 1.0f / (1.0f + __expf(-x0.y));- const float s80 = 1.0f / (1.0f + __expf(-x8.x));- const float s81 = 1.0f / (1.0f + __expf(-x8.y));+ const float s00 = sigmoid_fast(x0.x);+ const float s01 = sigmoid_fast(x0.y);+ const float s80 = sigmoid_fast(x8.x);+ const float s81 = sigmoid_fast(x8.y);o0.x = (x0.x * s00) * y0.x;o0.y = (x0.y * s01) * y0.y;o8.x = (x8.x * s80) * y8.x;⋯ 23 unchanged linesfloat2 o0;float2 o8;- const float s00 = 1.0f / (1.0f + __expf(-x0.x));- const float s01 = 1.0f / (1.0f + __expf(-x0.y));- const float s80 = 1.0f / (1.0f + __expf(-x8.x));- const float s81 = 1.0f / (1.0f + __expf(-x8.y));+ const float s00 = sigmoid_fast(x0.x);+ const float s01 = sigmoid_fast(x0.y);+ const float s80 = sigmoid_fast(x8.x);+ const float s81 = sigmoid_fast(x8.y);o0.x = (x0.x * s00) * y0.x;o0.y = (x0.y * s01) * y0.y;o8.x = (x8.x * s80) * y8.x;⋯ 11 unchanged lines}template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>+ __global__ __cluster_dims__(2, 1, 1) __launch_bounds__(BLOCK_M + 2 * WARP_SIZE)+ void dual_gemm_silu_mul_cluster_kernel(+ const __grid_constant__ CUtensorMap A_tmap,+ const __grid_constant__ CUtensorMap B1_tmap,+ const __grid_constant__ CUtensorMap B2_tmap,+ const char *SFA_ptr,+ const char *SFB1_ptr,+ const char *SFB2_ptr,+ half *Out_ptr,+ int M, int N+ ) {+ const int tid = threadIdx.x;++ const int lane_id = tid & 31;+ const int warp_id = tid >> 5;++ const int bid_m = (int)blockIdx.y;+ const int bid_n = (int)blockIdx.x;++ const int off_m = bid_m * BLOCK_M;+ const int off_n = bid_n * BLOCK_N;++ constexpr int NUM_WARPS = BLOCK_M / WARP_SIZE + 2;++ extern __shared__ __align__(1024) char smem_ptr[];+ const int smem = static_cast<int>(__cvta_generic_to_shared(smem_ptr));+ constexpr int A_size = BLOCK_M * BLOCK_K / 2;+ constexpr int B_size = BLOCK_N * BLOCK_K / 2;+ constexpr int SFA_size = 128 * BLOCK_K / 16;+ constexpr int SFB_size = 128 * BLOCK_K / 16;+ constexpr int STAGE_SIZE = A_size + (2 * B_size) + SFA_size + (2 * SFB_size);++ #pragma nv_diag_suppress static_var_with_dynamic_init+ __shared__ int64_t mbars[NUM_STAGES * 2 + 1];+ const int tma_mbar_addr = static_cast<int>(__cvta_generic_to_shared(mbars));+ const int mma_mbar_addr = tma_mbar_addr + NUM_STAGES * 8;+ const int mainloop_mbar_addr = mma_mbar_addr + NUM_STAGES * 8;++ constexpr int OUT1_tmem = 0;+ constexpr int OUT2_tmem = BLOCK_N;+ constexpr int SFA_tmem = 2 * BLOCK_N;+ constexpr int SFB1_tmem = SFA_tmem + 4 * (BLOCK_K / MMA_K);+ constexpr int SFB2_tmem = SFB1_tmem + 4 * (BLOCK_K / MMA_K);+ constexpr int TMEM_ALLOC = (BLOCK_N == 128) ? 512 : (BLOCK_N * 4);++ if (warp_id == 0 && elect_sync()) {+ for (int i = 0; i < NUM_STAGES * 2 + 1; i++) mbarrier_init(tma_mbar_addr + i * 8, 1);+ asm volatile("fence.mbarrier_init.release.cluster;");+ } else if (warp_id == 1) {+ asm volatile(+ "tcgen05.alloc.cta_group::1.sync.aligned.shared::cta.b32 [%0], %1;"+ :: "r"(smem), "r"(TMEM_ALLOC)+ );+ }+ __syncthreads();++ constexpr int num_iters = K / BLOCK_K;++ if (warp_id == NUM_WARPS - 2 && elect_sync()) {+ const uint64_t cache_A = EVICT_FIRST;+ const uint64_t cache_B = EVICT_FIRST;++ auto issue_tma = [&](int iter_k, int stage_id) {+ const int mbar_addr = tma_mbar_addr + stage_id * 8;+ const int A_smem = smem + stage_id * STAGE_SIZE;+ const int B1_smem = A_smem + A_size;+ const int B2_smem = B1_smem + B_size;+ const int SFA_smem = B2_smem + B_size;+ const int SFB1_smem = SFA_smem + SFA_size;+ const int SFB2_smem = SFB1_smem + SFB_size;++ const int off_k = iter_k * BLOCK_K;+ tma_3d_gmem2smem_cluster2(A_smem, &A_tmap, 0, off_m, off_k / 256, mbar_addr, cache_A);+ tma_3d_gmem2smem(B1_smem, &B1_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);+ tma_3d_gmem2smem(B2_smem, &B2_tmap, 0, off_n, off_k / 256, mbar_addr, cache_B);++ const int rest_k = K / 16 / 4;+ const char *SFA_src = SFA_ptr + ((off_m / 128) * rest_k + off_k / (16 * 4)) * 512;+ const char *SFB1_src = SFB1_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;+ const char *SFB2_src = SFB2_ptr + ((off_n / 128) * rest_k + off_k / (16 * 4)) * 512;+ tma_gmem2smem(SFA_smem, SFA_src, SFA_size, mbar_addr, cache_A);+ tma_gmem2smem(SFB1_smem, SFB1_src, SFB_size, mbar_addr, cache_B);+ tma_gmem2smem(SFB2_smem, SFB2_src, SFB_size, mbar_addr, cache_B);++ asm volatile(+ "mbarrier.arrive.expect_tx.release.cta.shared::cta.b64 _, [%0], %1;"+ :: "r"(mbar_addr), "r"(STAGE_SIZE)+ : "memory"+ );+ };++ constexpr int PRELOAD = (num_iters < NUM_STAGES) ? num_iters : NUM_STAGES;+ for (int iter_k = 0; iter_k < PRELOAD; iter_k++) issue_tma(iter_k, iter_k);+ for (int iter_k = NUM_STAGES; iter_k < num_iters; iter_k++) {+ const int stage_id = iter_k % NUM_STAGES;+ const int mma_phase = (iter_k / NUM_STAGES - 1) & 1;+ mbarrier_wait(mma_mbar_addr + stage_id * 8, mma_phase);+ issue_tma(iter_k, stage_id);+ }+ } else if (warp_id == NUM_WARPS - 1 && elect_sync()) {+ constexpr int MMA_N = BLOCK_N;+ constexpr int MMA_M = 128;+ constexpr uint32_t i_desc = (1U << 7U) | (1U << 10U) | ((uint32_t)MMA_N >> 3U << 17U) | ((uint32_t)MMA_M >> 7U << 27U);++ for (int iter_k = 0; iter_k < num_iters; iter_k++) {+ const int stage_id = iter_k % NUM_STAGES;+ const int tma_phase = (iter_k / NUM_STAGES) & 1;+ mbarrier_wait(tma_mbar_addr + stage_id * 8, tma_phase);++ const int A_smem = smem + stage_id * STAGE_SIZE;+ const int B1_smem = A_smem + A_size;+ const int B2_smem = B1_smem + B_size;+ const int SFA_smem = B2_smem + B_size;+ const int SFB1_smem = SFA_smem + SFA_size;+ const int SFB2_smem = SFB1_smem + SFB_size;++ auto make_desc_AB = [](int addr) -> uint64_t {+ const int SBO = 8 * 128;+ return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL) | (2ULL << 61ULL);+ };+ auto make_desc_SF = [](int addr) -> uint64_t {+ const int SBO = 8 * 16;+ return desc_encode(addr) | (desc_encode(SBO) << 32ULL) | (1ULL << 46ULL);+ };++ constexpr uint64_t SF_desc = make_desc_SF(0);+ const uint64_t SFA_desc = SF_desc + ((uint64_t)SFA_smem >> 4ULL);+ const uint64_t SFB1_desc = SF_desc + ((uint64_t)SFB1_smem >> 4ULL);+ const uint64_t SFB2_desc = SF_desc + ((uint64_t)SFB2_smem >> 4ULL);++ #pragma unroll+ for (int k = 0; k < BLOCK_K / MMA_K; k++) {+ const uint64_t sfa_desc = SFA_desc + (uint64_t)k * (512ULL >> 4ULL);+ const uint64_t sfb1_desc = SFB1_desc + (uint64_t)k * (512ULL >> 4ULL);+ const uint64_t sfb2_desc = SFB2_desc + (uint64_t)k * (512ULL >> 4ULL);+ tcgen05_cp_nvfp4(SFA_tmem + k * 4, sfa_desc);+ tcgen05_cp_nvfp4(SFB1_tmem + k * 4, sfb1_desc);+ tcgen05_cp_nvfp4(SFB2_tmem + k * 4, sfb2_desc);+ }++ const int sel_n = (bid_n % (128 / BLOCK_N)) * (BLOCK_N / 32);++ #pragma unroll+ for (int k1 = 0; k1 < BLOCK_K / 256; k1++) {+ #pragma unroll+ for (int k2 = 0; k2 < 256 / MMA_K; k2++) {+ const uint64_t a_desc = make_desc_AB(A_smem + k1 * BLOCK_M * 128 + k2 * 32);+ const uint64_t b1_desc = make_desc_AB(B1_smem + k1 * BLOCK_N * 128 + k2 * 32);+ const uint64_t b2_desc = make_desc_AB(B2_smem + k1 * BLOCK_N * 128 + k2 * 32);++ const int k_sf = k1 * 4 + k2;+ const int scale_A_tmem = SFA_tmem + k_sf * 4;+ const int scale_B1_tmem = SFB1_tmem + k_sf * 4 + sel_n;+ const int scale_B2_tmem = SFB2_tmem + k_sf * 4 + sel_n;++ const int enable_input_d = (k1 == 0 && k2 == 0) ? iter_k : 1;+ tcgen05_mma_nvfp4(OUT1_tmem, a_desc, b1_desc, i_desc, scale_A_tmem, scale_B1_tmem, enable_input_d);+ tcgen05_mma_nvfp4(OUT2_tmem, a_desc, b2_desc, i_desc, scale_A_tmem, scale_B2_tmem, enable_input_d);+ }+ }++ asm volatile(+ "tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"+ :: "r"(mma_mbar_addr + stage_id * 8)+ : "memory"+ );+ }++ asm volatile(+ "tcgen05.commit.cta_group::1.mbarrier::arrive::one.shared::cluster.b64 [%0];"+ :: "r"(mainloop_mbar_addr)+ : "memory"+ );+ } else if (tid < BLOCK_M) {+ mbarrier_wait(mainloop_mbar_addr, 0);+ asm volatile("tcgen05.fence::after_thread_sync;");++ constexpr int HALF_ITERS = 8;+ for (int mm = 0; mm < 2; mm++) {+ {+ float x[32];+ float y[32];+ tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 0);+ tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem);+ asm volatile("tcgen05.wait::ld.sync.aligned;");++ #pragma unroll+ for (int i = 0; i < HALF_ITERS; i++) {+ const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;+ const int col = off_n + i * 8 + (lane_id & 3) * 2;++ const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};+ const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};+ const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};+ const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};++ float2 o0;+ float2 o8;+ const float s00 = sigmoid_fast(x0.x);+ const float s01 = sigmoid_fast(x0.y);+ const float s80 = sigmoid_fast(x8.x);+ const float s81 = sigmoid_fast(x8.y);+ o0.x = (x0.x * s00) * y0.x;+ o0.y = (x0.y * s01) * y0.y;+ o8.x = (x8.x * s80) * y8.x;+ o8.y = (x8.y * s81) * y8.y;++ reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);+ reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);+ }+ }++ if constexpr (BLOCK_N == 128) {+ float x[32];+ float y[32];+ tcgen05_ld_16x256bx8(x, warp_id * 32 + mm * 16, 64);+ tcgen05_ld_16x256bx8(y, warp_id * 32 + mm * 16, OUT2_tmem + 64);+ asm volatile("tcgen05.wait::ld.sync.aligned;");++ #pragma unroll+ for (int i = 0; i < HALF_ITERS; i++) {+ const int row = off_m + warp_id * 32 + mm * 16 + lane_id / 4;+ const int col = off_n + 64 + i * 8 + (lane_id & 3) * 2;++ const float2 x0 = float2{x[i * 4 + 0], x[i * 4 + 1]};+ const float2 x8 = float2{x[i * 4 + 2], x[i * 4 + 3]};+ const float2 y0 = float2{y[i * 4 + 0], y[i * 4 + 1]};+ const float2 y8 = float2{y[i * 4 + 2], y[i * 4 + 3]};++ float2 o0;+ float2 o8;+ const float s00 = sigmoid_fast(x0.x);+ const float s01 = sigmoid_fast(x0.y);+ const float s80 = sigmoid_fast(x8.x);+ const float s81 = sigmoid_fast(x8.y);+ o0.x = (x0.x * s00) * y0.x;+ o0.y = (x0.y * s01) * y0.y;+ o8.x = (x8.x * s80) * y8.x;+ o8.y = (x8.y * s81) * y8.y;++ reinterpret_cast<half2 *>(Out_ptr + (row + 0) * N + col)[0] = __float22half2_rn(o0);+ reinterpret_cast<half2 *>(Out_ptr + (row + 8) * N + col)[0] = __float22half2_rn(o8);+ }+ }+ }++ asm volatile("bar.sync 1, %0;" :: "r"(BLOCK_M) : "memory");+ if (warp_id == 0) asm volatile("tcgen05.dealloc.cta_group::1.sync.aligned.b32 %0, %1;" :: "r"(0), "r"(TMEM_ALLOC));+ }+ }++ template <int K, int BLOCK_M, int BLOCK_N, int BLOCK_K, int NUM_STAGES>static inline void launch_gemm_f32(const at::Tensor& A,const at::Tensor& B,⋯ 97 unchanged linesconst CUtensorMap B1_tmap = cache_B1.get(B1_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);const CUtensorMap B2_tmap = cache_B2.get(B2_ptr, (uint64_t)N, (uint64_t)K, (uint32_t)BLOCK_N, (uint32_t)BLOCK_K);- dim3 grid(1, (unsigned)((M / BLOCK_M) * (N / BLOCK_N)));+ const int grid_x = N / BLOCK_N;+ const int grid_y = M / BLOCK_M;+ dim3 grid((unsigned)grid_x, (unsigned)grid_y);constexpr int tb_size = BLOCK_M + 2 * WARP_SIZE;constexpr int AB_size = (BLOCK_M + 2 * BLOCK_N) * (BLOCK_K / 2);constexpr int SF_size = 128 * (BLOCK_K / 16) * 3;constexpr int smem_size = (AB_size + SF_size) * NUM_STAGES;- auto kptr = dual_gemm_silu_mul_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;- static bool attr_set = false;- if (!attr_set) {- if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);- attr_set = true;+ if ((grid_x & 1) == 0) {+ auto kptr = dual_gemm_silu_mul_cluster_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;+ static bool attr_set = false;+ if (!attr_set) {+ if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);+ cudaFuncSetAttribute(kptr, cudaFuncAttributeNonPortableClusterSizeAllowed, 1);+ attr_set = true;+ }+ kptr<<<grid, tb_size, smem_size>>>(A_tmap, B1_tmap, B2_tmap, SFA_ptr, SFB1_ptr, SFB2_ptr, Out_ptr, M, N);+ } else {+ auto kptr = dual_gemm_silu_mul_kernel<K, BLOCK_M, BLOCK_N, BLOCK_K, NUM_STAGES>;+ static bool attr_set = false;+ if (!attr_set) {+ if constexpr (smem_size > 48'000) cudaFuncSetAttribute(kptr, cudaFuncAttributeMaxDynamicSharedMemorySize, smem_size);+ attr_set = true;+ }+ kptr<<<grid, tb_size, smem_size>>>(A_tmap, B1_tmap, B2_tmap, SFA_ptr, SFB1_ptr, SFB2_ptr, Out_ptr, M, N);}- kptr<<<grid, tb_size, smem_size>>>(A_tmap, B1_tmap, B2_tmap, SFA_ptr, SFB1_ptr, SFB2_ptr, Out_ptr, M, N);}__global__ void silu_mul_f32_vec2(const float* __restrict__ x, const float* __restrict__ y, half* __restrict__ out, int64_t n2) {⋯ 2 unchanged linesconst float2 fx = reinterpret_cast<const float2*>(x)[idx];const float2 fy = reinterpret_cast<const float2*>(y)[idx];float2 o;- const float sx0 = 1.0f / (1.0f + __expf(-fx.x));- const float sx1 = 1.0f / (1.0f + __expf(-fx.y));+ const float sx0 = sigmoid_fast(fx.x);+ const float sx1 = sigmoid_fast(fx.y);o.x = (fx.x * sx0) * fy.x;o.y = (fx.y * sx1) * fy.y;reinterpret_cast<half2*>(out)[idx] = __float22half2_rn(o);⋯ 144 unchanged linesif _loaded:returnload_inline(- name="nvfp4_dual_ext_tc_dual_fused_hostcache1",+ name="nvfp4_dual_ext_tc_dual_fused_final",cpp_sources="",cuda_sources=_CUDA_SRC,functions=None,
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Best evidence level for this revision: reported
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