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CUTLASS 3.7 (#2045)

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* 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
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tools/profiler/src/conv3d_operation_profiler.cu
+7 -73
View File
@@ -1,5 +1,5 @@
/***************************************************************************************************
* Copyright (c) 2017 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* Copyright (c) 2017 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
@@ -1148,8 +1148,6 @@ Status Conv3dOperationProfiler::profile_cutlass_(
void *host_workspace,
void *device_workspace) {
GpuTimer timer;
// initialize conv2d underlying operation to handle parallel reduction
library::Operation const* underlying_operation = operation;
@@ -1159,68 +1157,14 @@ Status Conv3dOperationProfiler::profile_cutlass_(
}
}
//
// Optional sleep to limit power consumption and thermals
//
sleep(options.profiling.sleep_duration);
//
// Warmup loop
//
Status status;
for (int iteration = 0; iteration < options.profiling.warmup_iterations; ++iteration) {
auto func = [&](cudaStream_t, int iteration) {
// Setup rotating workspace
int workspace_idx = options.profiling.warmup_iterations + iteration;
int problem_idx = (workspace_idx % conv_workspace_.problem_count);
int problem_idx = iteration % conv_workspace_.problem_count;
set_cutlass_operator_arguments_(problem_idx);
// Run underlying conv2d operation
status = underlying_operation->run(
arguments,
host_workspace,
device_workspace);
// Run parallel reduction kernel for parallel split_k_mode
if (conv_workspace_.configuration.split_k_mode == conv::SplitKMode::kParallel) {
status = reduction_op_->run(
&conv_workspace_.reduction_arguments,
conv_workspace_.reduction_host_workspace.data(),
nullptr);
}
if (status != Status::kSuccess) {
return status;
}
}
//
// Initialize GPU timer
//
timer.start();
//
// Profiling loop
//
int Iterations = options.profiling.iterations;
int iteration = 0;
for (; iteration < Iterations; ++iteration) {
// Setup rotating workspace
int problem_idx = (iteration % conv_workspace_.problem_count);
set_cutlass_operator_arguments_(problem_idx);
// Run underlying conv2d operation
status = underlying_operation->run(
Status status = underlying_operation->run(
arguments,
host_workspace,
device_workspace);
@@ -1236,21 +1180,11 @@ Status Conv3dOperationProfiler::profile_cutlass_(
if (status != Status::kSuccess) {
return status;
}
}
//
// Wait for completion
//
return status;
};
timer.stop_and_wait();
//
// Update performance result
//
result.runtime = timer.duration(iteration);
return status;
return profile_kernel_(result, options, func);
}
/////////////////////////////////////////////////////////////////////////////////////////////////