From 00e81e9eafe9b7b7a94f6f683096e1fcf2de6182 Mon Sep 17 00:00:00 2001 From: Zihao Ye Date: Wed, 11 Jan 2023 02:17:24 +0800 Subject: [PATCH] [Profiler] Allow user to flush L2 cache in `time_evalutor` function for profiling CUDA kernels (#13726) Currently, our default profiler (time_evaluator) does not flush the L2 cache per execution, this might lead to incorrect time measurement because the input data last run might reside in L2 cache and reduce the data fetching time in the next run. Both Triton and nvbench consider this effect thus reporting more accurate measurements. Solution: time_evalutor has an argument f_preproc where user can specify a pre-processing function per execution of the kernel being evaluated. Currently, TVM supports cache_flush_cpu_non_first_arg which flushes CPU cache. But similar functionality for GPU is missing. This PR completely borrows the design of nvbench's l2flush struct and allow the user to specify "l2_cache_flush_cuda" as a preprocessing function which flushes NVIDIA GPU's L2 cache. l2_cache_flush_cuda is not a default value so existing program's behavior would not be influenced. --- 3rdparty/nvbench/l2_cache_flush.h | 74 ++++++ LICENSE | 2 +- licenses/LICENSE.l2_cache_flush.txt | 218 ++++++++++++++++++ src/runtime/cuda/l2_cache_flush.cc | 42 ++++ .../unittest/test_evaluator_with_preproc.py | 60 +++++ 5 files changed, 395 insertions(+), 1 deletion(-) create mode 100644 3rdparty/nvbench/l2_cache_flush.h create mode 100644 licenses/LICENSE.l2_cache_flush.txt create mode 100644 src/runtime/cuda/l2_cache_flush.cc create mode 100644 tests/python/unittest/test_evaluator_with_preproc.py diff --git a/3rdparty/nvbench/l2_cache_flush.h b/3rdparty/nvbench/l2_cache_flush.h new file mode 100644 index 000000000000..3d0211564535 --- /dev/null +++ b/3rdparty/nvbench/l2_cache_flush.h @@ -0,0 +1,74 @@ +/* + * Copyright 2021 NVIDIA Corporation + * + * Licensed under the Apache License, Version 2.0 with the LLVM exception + * (the "License"); you may not use this file except in compliance with + * the License. + * + * You may obtain a copy of the License at + * + * http://llvm.org/foundation/relicensing/LICENSE.txt + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * \file l2_cache_flush.h + * \brief Functions to flush L2 cache using CUDA's API, adopted from nvbench. + */ +#ifndef L2_CACHE_FLUSH_H_ +#define L2_CACHE_FLUSH_H_ + +#include +#include +#include + +namespace tvm { +namespace runtime { + +#define CUDA_CALL(func) \ + { \ + cudaError_t e = (func); \ + ICHECK(e == cudaSuccess || e == cudaErrorCudartUnloading) \ + << "CUDA: " << cudaGetErrorString(e); \ + } + +class L2Flush { + public: + L2Flush() : initialized_(false), l2_size_(0), l2_buffer_(nullptr) {} + + ~L2Flush() { + if (l2_size_ > 0) { + CUDA_CALL(cudaFree(l2_buffer_)); + } + } + + void Flush(cudaStream_t stream) { + if (!initialized_) { + // initialize l2_buffer_ and l2_size_ + initialized_ = true; + int device_id; + CUDA_CALL(cudaGetDevice(&device_id)); + CUDA_CALL(cudaDeviceGetAttribute(&l2_size_, cudaDevAttrL2CacheSize, device_id)); + if (l2_size_ > 0) { + CUDA_CALL(cudaMalloc(reinterpret_cast(&l2_buffer_), l2_size_)); + } + } + if (l2_size_ > 0) { + CUDA_CALL(cudaMemsetAsync(l2_buffer_, 0, l2_size_, stream)); + } + } + + static L2Flush* ThreadLocal(); + + private: + bool initialized_ = false; + int l2_size_; + int* l2_buffer_; +}; + +} // namespace runtime +} // namespace tvm + +#endif // L2_CACHE_FLUSH_H_ diff --git a/LICENSE b/LICENSE index 6524d530deca..fbc11be2deb5 100644 --- a/LICENSE +++ b/LICENSE @@ -212,6 +212,7 @@ Apache Software Foundation License 2.0 3rdparty/dlpack 3rdparty/dmlc-core 3rdparty/OpenCL-Headers +3rdparty/nvbench (with LLVM exception) BSD 2-clause License @@ -234,7 +235,6 @@ MIT License 3rdparty/cma 3rdparty/compiler-rt/builtin_fp16.h - The Unlicense ------------- diff --git a/licenses/LICENSE.l2_cache_flush.txt b/licenses/LICENSE.l2_cache_flush.txt new file mode 100644 index 000000000000..bd8b243dfa02 --- /dev/null +++ b/licenses/LICENSE.l2_cache_flush.txt @@ -0,0 +1,218 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ +#include "../../../3rdparty/nvbench/l2_cache_flush.h" + +#include +#include +#include + +#include "cuda_common.h" + +namespace tvm { + +namespace runtime { + +typedef dmlc::ThreadLocalStore L2FlushStore; + +L2Flush* L2Flush::ThreadLocal() { return L2FlushStore::Get(); } + +TVM_REGISTER_GLOBAL("l2_cache_flush_cuda").set_body([](TVMArgs args, TVMRetValue* rv) { + ICHECK(L2Flush::ThreadLocal() != nullptr) << "L2Flush::ThreadLocal do not exist."; + cudaStream_t stream = CUDAThreadEntry::ThreadLocal()->stream; + L2Flush::ThreadLocal()->Flush(stream); +}); + +} // namespace runtime +} // namespace tvm diff --git a/tests/python/unittest/test_evaluator_with_preproc.py b/tests/python/unittest/test_evaluator_with_preproc.py new file mode 100644 index 000000000000..fc6eec25b8da --- /dev/null +++ b/tests/python/unittest/test_evaluator_with_preproc.py @@ -0,0 +1,60 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import tvm +from tvm import te +from tvm.script import tir as T +import tvm.testing +import numpy as np +import pytest + + +@T.prim_func +def matmul(a: T.handle, b: T.handle, c: T.handle) -> None: + A = T.match_buffer(a, [128, 128]) + B = T.match_buffer(b, [128, 128]) + C = T.match_buffer(c, [128, 128]) + for i, j, k in T.grid(128, 128, 128): + with T.block("matmul"): + vi, vj, vk = T.axis.remap("SSR", [i, j, k]) + with T.init(): + C[vi, vj] = 0.0 + C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vk, vj] + + +@tvm.testing.requires_cuda +@pytest.mark.parametrize("f_preproc", ["", "l2_cache_flush_cuda"]) +def test_time_evalutor_with_preproc(f_preproc: str): + mod = tvm.IRModule.from_expr(matmul) + sch = tvm.tir.Schedule(mod) + blk = sch.get_block("matmul") + i, j, k = sch.get_loops(blk) + sch.bind(i, "blockIdx.x") + sch.bind(j, "threadIdx.x") + f = tvm.build(sch.mod["main"], target="cuda") + dev = tvm.cuda(0) + evaluator = f.time_evaluator(f.entry_name, dev, repeat=1000, number=1, f_preproc=f_preproc) + + a = tvm.nd.array(np.random.rand(128, 128).astype("float32"), device=dev) + b = tvm.nd.array(np.random.rand(128, 128).astype("float32"), device=dev) + c = tvm.nd.array(np.zeros((128, 128)).astype("float32"), device=dev) + args = [a, b, c] + print("Evaluator (f_preproc={}):\t{:.5f}ms".format(f_preproc, evaluator(*args).mean * 1000)) + + +if __name__ == "__main__": + test_time_evalutor_with_preproc("l2_cache_flush_cuda")