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/***************************************************************************************************
* Copyright (c) 2017 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* 3. Neither the name of the copyright holder nor the names of its
* contributors may be used to endorse or promote products derived from
* this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/*! \file
\brief Statically sized array of elements that accommodates all CUTLASS-supported numeric types
and is safe to use in a union.
*/
#include "../common/cutlass_unit_test.h"
#include "cutlass/array.h"
#include "cutlass/util/device_memory.h"
#pragma warning( disable : 4800)
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace test {
namespace core {
/// Each thread clears its array and writes to global memory. No PRMT instructions should
/// be generated if Array<T, N> is a multiple of 32 bits.
template <typename T, int N>
__global__ void test_array_clear(cutlass::Array<T, N> *ptr) {
cutlass::Array<T, N> storage;
storage.clear();
ptr[threadIdx.x] = storage;
}
/// Each thread writes its thread index into the elements of its array and then writes the result
/// to global memory.
template <typename T, int N>
__global__ void test_array_threadid(cutlass::Array<T, N> *ptr) {
cutlass::Array<T, N> storage;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
storage.at(i) = T(int(threadIdx.x));
}
ptr[threadIdx.x] = storage;
}
/// Each thread writes its thread index into the elements of its array and then writes the result
/// to global memory.
template <typename T, int N>
__global__ void test_array_sequence(cutlass::Array<T, N> *ptr) {
cutlass::Array<T, N> storage;
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N; ++i) {
storage.at(i) = T(i);
}
ptr[threadIdx.x] = storage;
}
} // namespace core
} // namespace test
/////////////////////////////////////////////////////////////////////////////////////////////////
template <typename T, int N>
class TestArray {
public:
//
// Data members
//
/// Number of threads
int const kThreads = 32;
typedef cutlass::Array<T, N> ArrayTy;
//
// Methods
//
/// Ctor
TestArray() {
}
/// Runs the test
void run() {
/// Device memory containing output
cutlass::device_memory::allocation< ArrayTy > output(kThreads);
std::vector< ArrayTy > output_host(kThreads);
dim3 grid(1,1);
dim3 block(kThreads, 1, 1);
test::core::test_array_clear<<< grid, block >>>(output.get());
cudaError_t result = cudaDeviceSynchronize();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
//
// Verify contains all zeros
//
cutlass::device_memory::copy_to_host(output_host.data(), output.get(), kThreads);
result = cudaGetLastError();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
char const *ptr_host = reinterpret_cast<char const *>(output_host.data());
for (int i = 0; i < sizeof(ArrayTy) * kThreads; ++i) {
EXPECT_FALSE(ptr_host[i]);
}
//
// Verify each element contains the low bits of the thread Id
//
test::core::test_array_threadid<<< grid, block >>>(output.get());
result = cudaDeviceSynchronize();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
cutlass::device_memory::copy_to_host(output_host.data(), output.get(), kThreads);
result = cudaGetLastError();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
for (int i = 0; i < kThreads; ++i) {
T tid = T(i);
ArrayTy thread = output_host.at(i);
// Element-wise access
for (int j = 0; j < N; ++j) {
EXPECT_TRUE(tid == thread[j]);
}
// Iterator access
for (auto it = thread.begin(); it != thread.end(); ++it) {
EXPECT_TRUE(tid == *it);
}
// Range-based for
for (auto const & x : thread) {
EXPECT_TRUE(tid == x);
}
}
//
// Verify each element
//
test::core::test_array_sequence<<< grid, block >>>(output.get());
result = cudaDeviceSynchronize();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
cutlass::device_memory::copy_to_host(output_host.data(), output.get(), kThreads);
result = cudaGetLastError();
ASSERT_EQ(result, cudaSuccess) << "CUDA error: " << cudaGetErrorString(result);
for (int i = 0; i < kThreads; ++i) {
ArrayTy thread = output_host.at(i);
// Element-wise access
for (int j = 0; j < N; ++j) {
T got = T(j);
EXPECT_TRUE(got == thread[j]);
}
// Iterator access
int j = 0;
for (auto it = thread.begin(); it != thread.end(); ++it, ++j) {
T got = T(j);
EXPECT_TRUE(got == *it);
}
// Range-based for
j = 0;
for (auto const & x : thread) {
T got = T(j);
EXPECT_TRUE(got == x);
++j;
}
}
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
TEST(Array, Int8x16) {
TestArray<int8_t, 16>().run();
}
TEST(Array, Int32x4) {
TestArray<int, 4>().run();
}
#if __CUDA_ARCH__ >= 520
TEST(Array, Float16x8) {
TestArray<cutlass::half_t, 8>().run();
}
#endif
TEST(Array, FloatBF16x8) {
TestArray<cutlass::bfloat16_t, 8>().run();
}
TEST(Array, FloatTF32x4) {
TestArray<cutlass::tfloat32_t, 4>().run();
}
TEST(Array, Float32x4) {
TestArray<float, 4>().run();
}
TEST(Array, Int4x32) {
TestArray<cutlass::int4b_t, 32>().run();
}
TEST(Array, Uint4x32) {
TestArray<cutlass::uint4b_t, 32>().run();
}
TEST(Array, Bin1x128) {
TestArray<cutlass::bin1_t, 128>().run();
}
/////////////////////////////////////////////////////////////////////////////////////////////////
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