leavelet/cutlass
1
0
Fork 0
Code Issues Pull Requests Actions 29 Packages Projects Releases Wiki Activity

CUTLASS 3.7 (#2045)

Browse Source 
* CUTLASS 3.7

* clean up changelog

---------

Co-authored-by: yuzhai <yuzhai@nvidia.com>
Co-authored-by: Haicheng Wu <haichengw@nvidia.com>
This commit is contained in:
Yujia Zhai
2025-01-18 09:53:07 -05:00
committed by GitHub
co-authored by yuzhai Haicheng Wu
parent 902dff3663
commit b78588d163
2030 changed files with 8947 additions and 3475 deletions
Download Patch File Download Diff File Expand all files Collapse all files
examples/62_hopper_sparse_gemm/62_hopper_sparse_gemm.cu
+39 -32
View File
@@ -1,5 +1,5 @@
/***************************************************************************************************
* Copyright (c) 2024 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* Copyright (c) 2024 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
@@ -92,15 +92,15 @@ using ElementAccumulator = float; // E
using TileShape = Shape<_128,_128,_128>; // Threadblock-level tile size for sparse kernel
using TileShapeRef = Shape<_128,_128, _64>; // Threadblock-level tile size for reference (dense) kernel
using ClusterShape = Shape<_1,_2,_1>; // Shape of the threadblocks in a cluster
using KernelSchedule = cutlass::gemm::KernelTmaWarpSpecialized; // Kernel schedule policy
using EpilogueSchedule = cutlass::epilogue::TmaWarpSpecialized; // Epilogue schedule policy
using KernelSchedule = cutlass::gemm::collective::KernelScheduleAuto; // Kernel schedule policy
using EpilogueSchedule = cutlass::epilogue::collective::EpilogueScheduleAuto; // Epilogue schedule policy
using ProblemShape = Shape<int,int,int,int>;
// Sparse kernel setup
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::arch::Sm90, cutlass::arch::OpClassSparseTensorOp,
TileShape, ClusterShape,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAccumulator, ElementAccumulator,
@@ -224,18 +224,12 @@ cutlass::DeviceAllocation<typename Gemm::EpilogueOutputOp::ElementOutput> block_
// Command line options parsing
struct Options {
bool help;
bool help = false;
float alpha, beta;
int iterations;
int m, n, k, l;
Options():
help(false),
m(5120), n(4096), k(16384), l(1),
alpha(1.f), beta(0.f),
iterations(10)
{ }
float alpha = 1.f, beta = 0.f;
int iterations = 100;
int warmup = 100;
int m = 5120, n = 4096, k = 16384, l = 1;
// Parses the command line
void parse(int argc, char const **args) {
@@ -253,26 +247,32 @@ struct Options {
cmd.get_cmd_line_argument("alpha", alpha);
cmd.get_cmd_line_argument("beta", beta);
cmd.get_cmd_line_argument("iterations", iterations);
cmd.get_cmd_line_argument("warmup", warmup);
}
/// Prints the usage statement.
std::ostream & print_usage(std::ostream &out) const {
out << "62_hopper_sparse_gemm\n\n"
<< " Hopper Sparse GEMM example.\n\n"
<< "Options:\n\n"
<< " --help If specified, displays this usage statement\n\n"
<< " --m=<int> Sets the M extent of the GEMM\n"
<< " --n=<int> Sets the N extent of the GEMM\n"
<< " --k=<int> Sets the K extent of the GEMM\n"
<< " --l=<int> Sets the L extent of the GEMM (batch size)\n"
<< " --alpha=<f32> Epilogue scalar alpha\n"
<< " --beta=<f32> Epilogue scalar beta\n\n"
<< " --iterations=<int> Number of profiling iterations to perform.\n\n";
out
<< "\n\nExamples:\n\n"
<< "$ " << "62_hopper_sparse_gemm" << " --m=4096 --n=5120 --k=8192 --l=1 --alpha=2 --beta=0.707 \n\n";
out << "62_hopper_sparse_gemm\n"
"\n"
" Hopper Sparse GEMM example.\n"
"\n"
"Options:\n"
"\n"
" --help If specified, displays this usage statement\n\n"
" --m=<int> Sets the M extent of the GEMM\n"
" --n=<int> Sets the N extent of the GEMM\n"
" --k=<int> Sets the K extent of the GEMM\n"
" --l=<int> Sets the L extent of the GEMM (batch size)\n"
" --alpha=<f32> Epilogue scalar alpha\n"
" --beta=<f32> Epilogue scalar beta\n"
" --iterations=<int> Number of profiling iterations to perform.\n"
" --warmup=<int> Number of warmup iterations to perform.\n"
"\n"
"Examples:\n"
"\n"
"62_hopper_sparse_gemm --m=4096 --n=5120 --k=8192 --l=1 --alpha=2 --beta=0.707\n"
"\n";
return out;
}
@@ -442,7 +442,6 @@ void print_device_tensor(cute::Tensor<Engine, Layout> const& t)
}
bool verify(Options const& options) {
CUDA_CHECK(cudaDeviceSynchronize());
bool passed = cutlass::reference::device::BlockCompareEqual(block_D_ref.get(), block_D.get(), block_D.size());
@@ -492,6 +491,10 @@ struct Runner
void benchmark(Options const& options) {
if (options.iterations > 0)
{
for (int iter = 0; iter < options.warmup; ++iter) {
run();
}
GpuTimer timer;
timer.start();
for (int iter = 0; iter < options.iterations; ++iter) {
@@ -525,12 +528,16 @@ void run(Options &options) {
Runner<Gemm> gemm(make_args(options));
Runner<GemmRef> gemm_ref(make_args_ref(options));
std::cout << " Problem Size: " << options.m << 'x' << options.n << 'x' << options.k << 'x' << options.l << std::endl;
gemm.run();
CUDA_CHECK(cudaDeviceSynchronize());
gemm_ref.run();
CUDA_CHECK(cudaDeviceSynchronize());
bool passed = verify(options);
std::cout << " Problem Size: " << options.m << 'x' << options.n << 'x' << options.k << std::endl;
std::cout << " Disposition: " << (passed ? "Passed" : "Failed") << std::endl;
if (!passed) {
examples/62_hopper_sparse_gemm/CMakeLists.txt
+1 -1
View File
@@ -1,5 +1,5 @@
# Copyright (c) 2024 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# Copyright (c) 2024 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without