439 lines
13 KiB
Plaintext
439 lines
13 KiB
Plaintext
/***************************************************************************************************
|
|
* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without modification, are permitted
|
|
* provided that the following conditions are met:
|
|
* * Redistributions of source code must retain the above copyright notice, this list of
|
|
* conditions and the following disclaimer.
|
|
* * 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.
|
|
* * Neither the name of the NVIDIA CORPORATION 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 NVIDIA CORPORATION 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 Tests for device-wide GEMV interface
|
|
*/
|
|
|
|
#include <iostream>
|
|
#include <fstream>
|
|
#include <sstream>
|
|
|
|
#include "cutlass/cutlass.h"
|
|
#include "cutlass/gemm/kernel/gemv.h"
|
|
#include "cutlass/gemm/device/gemv.h"
|
|
|
|
#include "../../common/cutlass_unit_test.h"
|
|
|
|
#include "cutlass/util/host_tensor.h"
|
|
#include "cutlass/util/tensor_view_io.h"
|
|
#include "cutlass/util/distribution.h"
|
|
#include "cutlass/util/reference/host/tensor_fill.h"
|
|
#include "cutlass/util/reference/host/tensor_copy.h"
|
|
#include "cutlass/util/reference/host/tensor_compare.h"
|
|
#include "cutlass/util/reference/host/tensor_norm.h"
|
|
#include "cutlass/util/reference/host/gemm.h"
|
|
#include "cutlass/util/reference/host/gemm_complex.h"
|
|
|
|
#include "testbed_utils.h"
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
namespace test {
|
|
namespace gemm {
|
|
|
|
template <typename Gemv>
|
|
class TestbedGemv {
|
|
public:
|
|
|
|
using ElementA = typename Gemv::ElementA;
|
|
using LayoutA = typename Gemv::LayoutA;
|
|
using ElementB = typename Gemv::ElementB;
|
|
using ElementC = typename Gemv::ElementC;
|
|
|
|
using ElementAccumulator = typename Gemv::ElementAccumulator;
|
|
using ElementCompute = typename Gemv::EpilogueOutputOp::ElementCompute;
|
|
|
|
using LayoutV = cutlass::layout::RowMajor;
|
|
|
|
private:
|
|
|
|
/// Initialization
|
|
cutlass::Distribution::Kind init_A;
|
|
cutlass::Distribution::Kind init_B;
|
|
cutlass::Distribution::Kind init_C;
|
|
uint64_t seed;
|
|
|
|
cutlass::HostTensor<ElementA, LayoutA> tensor_A;
|
|
cutlass::HostTensor<ElementB, LayoutV> tensor_B;
|
|
cutlass::HostTensor<ElementC, LayoutV> tensor_C;
|
|
cutlass::HostTensor<ElementC, LayoutV> tensor_D;
|
|
cutlass::HostTensor<ElementC, LayoutV> reference_D;
|
|
|
|
public:
|
|
|
|
//
|
|
// Methods
|
|
//
|
|
|
|
TestbedGemv(
|
|
cutlass::Distribution::Kind init_A_ = cutlass::Distribution::Uniform,
|
|
cutlass::Distribution::Kind init_B_ = cutlass::Distribution::Uniform,
|
|
cutlass::Distribution::Kind init_C_ = cutlass::Distribution::Uniform,
|
|
uint64_t seed_ = 2080
|
|
):
|
|
init_A(init_A_), init_B(init_B_), init_C(init_C_), seed(seed_) { }
|
|
|
|
/// Helper to initialize a tensor view
|
|
template <typename Element, typename Layout>
|
|
bool initialize_tensor(
|
|
cutlass::TensorView<Element, Layout> view,
|
|
cutlass::Distribution::Kind dist_kind,
|
|
uint64_t seed) {
|
|
|
|
if (dist_kind == cutlass::Distribution::Uniform) {
|
|
|
|
double scope_max, scope_min;
|
|
int bits_input = cutlass::sizeof_bits<Element>::value;
|
|
int bits_output = cutlass::sizeof_bits<typename Gemv::ElementC>::value;
|
|
|
|
if (bits_input == 1) {
|
|
scope_max = 2;
|
|
scope_min = 0;
|
|
} else if (bits_input <= 8) {
|
|
scope_max = 2;
|
|
scope_min = -2;
|
|
} else if (bits_output == 16) {
|
|
scope_max = 5;
|
|
scope_min = -5;
|
|
} else {
|
|
scope_max = 8;
|
|
scope_min = -8;
|
|
}
|
|
|
|
cutlass::reference::host::TensorFillRandomUniform(
|
|
view, seed, scope_max, scope_min, 0);
|
|
}
|
|
else if (dist_kind == cutlass::Distribution::Identity) {
|
|
|
|
cutlass::reference::host::TensorFillIdentity(view);
|
|
}
|
|
else if (dist_kind == cutlass::Distribution::Gaussian) {
|
|
|
|
cutlass::reference::host::TensorFillRandomGaussian(view, seed, 0, 0.5);
|
|
}
|
|
else if (dist_kind == cutlass::Distribution::Sequential) {
|
|
|
|
cutlass::reference::host::BlockFillSequential(
|
|
view.data(), view.capacity());
|
|
}
|
|
else {
|
|
// TODO: Implement the rest
|
|
EXPECT_TRUE(false) << "Not implemented";
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
/// Initializes data structures
|
|
void initialize(
|
|
cutlass::MatrixCoord problem_size
|
|
) {
|
|
|
|
//
|
|
// Allocate the GEMM workspace
|
|
//
|
|
|
|
tensor_A.resize(problem_size);
|
|
tensor_B.resize({problem_size.column(), 1});
|
|
tensor_C.resize({problem_size.row(), 1});
|
|
tensor_D.resize({problem_size.row(), 1});
|
|
reference_D.resize({problem_size.row(), 1}, false);
|
|
|
|
EXPECT_TRUE(initialize_tensor(tensor_A.host_view(), init_A, seed + 2019));
|
|
EXPECT_TRUE(initialize_tensor(tensor_B.host_view(), init_B, seed + 2018));
|
|
EXPECT_TRUE(initialize_tensor(tensor_C.host_view(), init_C, seed + 2017));
|
|
|
|
// It is possible to randomly initialize to all zeros, so override this with non-zeros
|
|
// in the upper left corner of each operand.
|
|
tensor_A.host_view().at({0, 0}) = typename Gemv::ElementA(1);
|
|
tensor_B.host_view().at({0, 0}) = typename Gemv::ElementB(1);
|
|
tensor_C.host_view().at({0, 0}) = typename Gemv::ElementC(1);
|
|
|
|
cutlass::reference::host::TensorCopy(reference_D.host_view(), tensor_C.host_view());
|
|
|
|
tensor_A.sync_device();
|
|
tensor_B.sync_device();
|
|
tensor_C.sync_device();
|
|
tensor_D.sync_device();
|
|
}
|
|
|
|
/// Compares computed reference with device reference and outputs to a file if incorrect
|
|
bool compare_reference(
|
|
cutlass::MatrixCoord problem_size,
|
|
ElementCompute alpha,
|
|
ElementCompute beta) {
|
|
|
|
tensor_D.sync_host();
|
|
|
|
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_A.host_view()), 0);
|
|
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_B.host_view()), 0);
|
|
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_C.host_view()), 0);
|
|
|
|
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_D.host_view()), 0);
|
|
EXPECT_GT(cutlass::reference::host::TensorNorm(reference_D.host_view()), 0);
|
|
|
|
bool passed = cutlass::reference::host::TensorEquals(reference_D.host_view(), tensor_D.host_view());
|
|
|
|
EXPECT_TRUE(passed) << " mismatched reference";
|
|
|
|
if (!passed) {
|
|
|
|
std::ofstream file("testbed_universal_errors.txt");
|
|
|
|
file
|
|
<< "problem: " << problem_size
|
|
<< ", alpha: " << alpha << ", beta: " << beta << "\n\n";
|
|
|
|
file
|
|
<< "A =\n" << tensor_A.host_view()
|
|
<< "\nB =\n" << tensor_B.host_view()
|
|
<< "\nC =\n" << tensor_C.host_view()
|
|
<< "\n\nReference =\n" << reference_D.host_view()
|
|
<< "\nComputed =\n" << tensor_D.host_view();
|
|
}
|
|
|
|
return passed;
|
|
}
|
|
|
|
/// Verifies the result is a GEMM
|
|
bool verify(
|
|
cutlass::MatrixCoord problem_size,
|
|
ElementCompute alpha,
|
|
ElementCompute beta) {
|
|
|
|
//
|
|
// Verify
|
|
//
|
|
|
|
cutlass::reference::host::GemmComplex<
|
|
typename Gemv::ElementA, typename Gemv::LayoutA,
|
|
typename Gemv::ElementB, LayoutV,
|
|
typename Gemv::ElementC, LayoutV,
|
|
ElementCompute, ElementAccumulator
|
|
>(
|
|
{problem_size.row(), 1, problem_size.column()},
|
|
alpha,
|
|
tensor_A.host_ref(),
|
|
Gemv::kTransformA,
|
|
tensor_B.host_ref(),
|
|
Gemv::kTransformB,
|
|
beta,
|
|
tensor_C.host_ref(),
|
|
reference_D.host_ref(),
|
|
ElementAccumulator(0)
|
|
);
|
|
|
|
return compare_reference(problem_size, alpha, beta);
|
|
}
|
|
|
|
/// Runs one problem size
|
|
bool run(
|
|
cutlass::MatrixCoord problem_size,
|
|
ElementCompute alpha,
|
|
ElementCompute beta) {
|
|
|
|
this->initialize(problem_size);
|
|
|
|
//
|
|
// Initialize the GEMM operator
|
|
//
|
|
|
|
typename Gemv::Arguments arguments{
|
|
problem_size,
|
|
{alpha, beta},
|
|
tensor_A.device_ref(),
|
|
tensor_B.device_data(),
|
|
tensor_C.device_data(),
|
|
tensor_D.device_data(),
|
|
tensor_B.layout().stride(0),
|
|
tensor_C.layout().stride(0),
|
|
tensor_D.layout().stride(0)
|
|
};
|
|
|
|
Gemv gemm_op;
|
|
|
|
size_t workspace_size = Gemv::get_workspace_size(arguments);
|
|
|
|
cutlass::device_memory::allocation<uint8_t> workspace(workspace_size);
|
|
|
|
cutlass::Status status = gemm_op.initialize(arguments, workspace.get());
|
|
|
|
EXPECT_TRUE(status == cutlass::Status::kSuccess) << to_string(status);
|
|
|
|
//
|
|
// Run the GEMM
|
|
//
|
|
|
|
status = gemm_op();
|
|
|
|
EXPECT_TRUE(status == cutlass::Status::kSuccess) << to_string(status);
|
|
|
|
//
|
|
// Verify
|
|
//
|
|
|
|
bool passed = this->verify(problem_size, alpha, beta);
|
|
|
|
return passed;
|
|
}
|
|
};
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
template <typename Gemv>
|
|
bool TestAllGemv() {
|
|
|
|
using ElementCompute = typename Gemv::EpilogueOutputOp::ElementCompute;
|
|
|
|
int M[] = {
|
|
8, 48, 192, 520
|
|
};
|
|
|
|
int K[] = {
|
|
8, 192, 528
|
|
};
|
|
|
|
double Alpha[] = {
|
|
1, 1.25
|
|
};
|
|
|
|
double Beta[] = {
|
|
0, 1, 1.25
|
|
};
|
|
|
|
for (int m : M) {
|
|
for (int k : K) {
|
|
for (double alpha : Alpha) {
|
|
for (double beta : Beta) {
|
|
|
|
TestbedGemv<Gemv> testbed;
|
|
|
|
if (!testbed.run({m, k}, ElementCompute(alpha), ElementCompute(beta))) {
|
|
return false;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
} // namespace gemm
|
|
} // namespace test
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM50_Device_Gemv_f32n_f32_f32_simt_f32, Simple) {
|
|
|
|
using ElementOutput = float;
|
|
using LayoutA = cutlass::layout::ColumnMajor;
|
|
using ElementAccumulator = float;
|
|
|
|
using EpilogueOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
1,
|
|
ElementAccumulator,
|
|
ElementAccumulator>;
|
|
|
|
using Gemv = cutlass::gemm::device::Gemv<
|
|
cutlass::gemm::kernel::Gemv<
|
|
ElementOutput, // Element A
|
|
LayoutA, // Layout A
|
|
ElementOutput, // Element B
|
|
ElementOutput, // Element C
|
|
ElementAccumulator, // Element Accumulator
|
|
EpilogueOp // Output operator
|
|
>
|
|
>;
|
|
|
|
|
|
EXPECT_TRUE(test::gemm::TestAllGemv<Gemv>());
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM50_Device_Gemv_f16n_f16_f32_simt_f32, Simple) {
|
|
|
|
using ElementInput = cutlass::half_t;
|
|
using ElementOutput = float;
|
|
using LayoutA = cutlass::layout::ColumnMajor;
|
|
using ElementAccumulator = float;
|
|
|
|
using EpilogueOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
1,
|
|
ElementAccumulator,
|
|
ElementAccumulator>;
|
|
|
|
using Gemv = cutlass::gemm::device::Gemv<
|
|
cutlass::gemm::kernel::Gemv<
|
|
ElementInput, // Element A
|
|
LayoutA, // Layout A
|
|
ElementInput, // Element B
|
|
ElementOutput, // Element C
|
|
ElementAccumulator, // Element Accumulator
|
|
EpilogueOp // Output operator
|
|
>
|
|
>;
|
|
|
|
|
|
EXPECT_TRUE(test::gemm::TestAllGemv<Gemv>());
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM50_Device_Gemv_f16n_f16_f16_simt_f32, Simple) {
|
|
|
|
using ElementInput = cutlass::half_t;
|
|
using ElementOutput = cutlass::half_t;
|
|
using LayoutA = cutlass::layout::ColumnMajor;
|
|
using ElementAccumulator = float;
|
|
|
|
using EpilogueOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
1,
|
|
ElementAccumulator,
|
|
ElementAccumulator>;
|
|
|
|
using Gemv = cutlass::gemm::device::Gemv<
|
|
cutlass::gemm::kernel::Gemv<
|
|
ElementInput, // Element A
|
|
LayoutA, // Layout A
|
|
ElementInput, // Element B
|
|
ElementOutput, // Element C
|
|
ElementAccumulator, // Element Accumulator
|
|
EpilogueOp // Output operator
|
|
>
|
|
>;
|
|
|
|
|
|
EXPECT_TRUE(test::gemm::TestAllGemv<Gemv>());
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|