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new 4119c9fecd [REFACTOR][CUDA] Phase out l2 cache flush preproc test
(#19768)
4119c9fecd is described below
commit 4119c9fecd1b4d487721fa56848f95eef914ca7f
Author: Tianqi Chen <[email protected]>
AuthorDate: Sun Jun 14 17:18:43 2026 -0400
[REFACTOR][CUDA] Phase out l2 cache flush preproc test (#19768)
The CUDA-specific timer preprocessor test was the only user of the
nvbench-derived L2 cache flush helper. Removing that path avoids
carrying a special CUDA registration and third-party header for
benchmark-only test coverage.
This PR removes the CUDA L2 cache flush registration, the dedicated
preprocessor timing test, and the now-unused nvbench-derived
license/dependency entry.
---
3rdparty/nvbench/l2_cache_flush.h | 74 -------
LICENSE | 1 -
licenses/LICENSE.l2_cache_flush.txt | 218 ---------------------
src/backend/cuda/runtime/l2_cache_flush.cc | 49 -----
.../python/runtime/test_evaluator_with_preproc.py | 60 ------
5 files changed, 402 deletions(-)
diff --git a/3rdparty/nvbench/l2_cache_flush.h
b/3rdparty/nvbench/l2_cache_flush.h
deleted file mode 100644
index 42031fc009..0000000000
--- a/3rdparty/nvbench/l2_cache_flush.h
+++ /dev/null
@@ -1,74 +0,0 @@
-/*
- * 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 <cuda.h>
-#include <cuda_runtime.h>
-#include <tvm/runtime/logging.h>
-
-namespace tvm {
-namespace runtime {
-
-#define CUDA_CALL(func) \
- { \
- cudaError_t e = (func); \
- TVM_FFI_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<void**>(&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 28d0627c1a..94abb3512b 100644
--- a/LICENSE
+++ b/LICENSE
@@ -210,7 +210,6 @@ Apache Software Foundation License 2.0
--------------------------------------
3rdparty/OpenCL-Headers
-3rdparty/nvbench (with LLVM exception)
3rdparty/cutlass_fpA_intB_gemm
3rdparty/tensorrt_llm
3rdparty/tvm-ffi/3rdparty/dlpack
diff --git a/licenses/LICENSE.l2_cache_flush.txt
b/licenses/LICENSE.l2_cache_flush.txt
deleted file mode 100644
index bd8b243dfa..0000000000
--- a/licenses/LICENSE.l2_cache_flush.txt
+++ /dev/null
@@ -1,218 +0,0 @@
- Apache License
- Version 2.0, January 2004
- http://www.apache.org/licenses/
-
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-
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- "control" means (i) the power, direct or indirect, to cause the
- direction or management of such entity, whether by contract or
- otherwise, or (ii) ownership of fifty percent (50%) or more of the
- outstanding shares, or (iii) beneficial ownership of such entity.
-
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- Unless required by applicable law or agreed to in writing, software
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diff --git a/src/backend/cuda/runtime/l2_cache_flush.cc
b/src/backend/cuda/runtime/l2_cache_flush.cc
deleted file mode 100644
index ca6987733c..0000000000
--- a/src/backend/cuda/runtime/l2_cache_flush.cc
+++ /dev/null
@@ -1,49 +0,0 @@
-/*
- * 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.
- */
-#include "../../../../3rdparty/nvbench/l2_cache_flush.h"
-
-#include <tvm/ffi/extra/c_env_api.h>
-#include <tvm/ffi/function.h>
-#include <tvm/ffi/reflection/registry.h>
-#include <tvm/runtime/device_api.h>
-
-#include "cuda_common.h"
-
-namespace tvm {
-
-namespace runtime {
-
-L2Flush* L2Flush::ThreadLocal() {
- static thread_local L2Flush inst;
- return &inst;
-}
-
-TVM_FFI_STATIC_INIT_BLOCK() {
- namespace refl = tvm::ffi::reflection;
- refl::GlobalDef().def_packed("l2_cache_flush_cuda", [](ffi::PackedArgs args,
ffi::Any* rv) {
- TVM_FFI_ICHECK(L2Flush::ThreadLocal() != nullptr) << "L2Flush::ThreadLocal
do not exist.";
- int device_id;
- CUDA_CALL(cudaGetDevice(&device_id));
- cudaStream_t stream =
static_cast<cudaStream_t>(TVMFFIEnvGetStream(kDLCUDA, device_id));
- L2Flush::ThreadLocal()->Flush(stream);
- });
-}
-
-} // namespace runtime
-} // namespace tvm
diff --git a/tests/python/runtime/test_evaluator_with_preproc.py
b/tests/python/runtime/test_evaluator_with_preproc.py
deleted file mode 100644
index ad535beea1..0000000000
--- a/tests/python/runtime/test_evaluator_with_preproc.py
+++ /dev/null
@@ -1,60 +0,0 @@
-# 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 numpy as np
-import pytest
-
-import tvm
-import tvm.testing
-from tvm.script import tirx as T
-
-
[email protected]_func(s_tir=True)
-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.sblock("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]
-
-
[email protected]_cuda
[email protected]("f_preproc", ["", "l2_cache_flush_cuda"])
-def test_time_evalutor_with_preproc(f_preproc: str):
- mod = tvm.IRModule.from_expr(matmul.with_attr("global_symbol", "main"))
- sch = tvm.s_tir.Schedule(mod)
- blk = sch.get_sblock("matmul")
- i, j, k = sch.get_loops(blk)
- sch.bind(i, "blockIdx.x")
- sch.bind(j, "threadIdx.x")
- f = tvm.tirx.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.runtime.tensor(np.random.rand(128, 128).astype("float32"),
device=dev)
- b = tvm.runtime.tensor(np.random.rand(128, 128).astype("float32"),
device=dev)
- c = tvm.runtime.tensor(np.zeros((128, 128)).astype("float32"), device=dev)
- args = [a, b, c]
- print(f"Evaluator (f_preproc={f_preproc}):\t{evaluator(*args).mean *
1000:.5f}ms")
-
-
-if __name__ == "__main__":
- test_time_evalutor_with_preproc("l2_cache_flush_cuda")
