CUTLASS 2.0 (#62)
CUTLASS 2.0 Substantially refactored for - Better performance, particularly for native Turing Tensor Cores - Robust and durable templates spanning the design space - Encapsulated functionality embodying modern C++11 programming techniques - Optimized containers and data types for efficient, generic, portable device code Updates to: - Quick start guide - Documentation - Utilities - CUTLASS Profiler Native Turing Tensor Cores - Efficient GEMM kernels targeting Turing Tensor Cores - Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands Coverage of existing CUTLASS functionality: - GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs - Volta Tensor Cores through native mma.sync and through WMMA API - Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions - Batched GEMM operations - Complex-valued GEMMs Note: this commit and all that follow require a host compiler supporting C++11 or greater.
This commit is contained in:
Andrew Kerr
@@ -0,0 +1,27 @@
|
||||
# Copyright (c) 2017-2019, 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 TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
||||
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
|
||||
cutlass_test_unit_add_executable(
|
||||
cutlass_test_unit_reduction_thread
|
||||
reduction_thread.cu
|
||||
testbed.h
|
||||
)
|
||||
@@ -0,0 +1,94 @@
|
||||
/***************************************************************************************************
|
||||
* Copyright (c) 2017-2019, 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 TOR (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 Unit tests for thread-level Reduction
|
||||
*/
|
||||
|
||||
#include "../../common/cutlass_unit_test.h"
|
||||
|
||||
#include "testbed.h"
|
||||
|
||||
/////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
|
||||
TEST(Reduce_thread_device, Reduce_half_t_1) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_device<
|
||||
cutlass::half_t,
|
||||
1
|
||||
>().run();
|
||||
}
|
||||
|
||||
TEST(Reduce_thread_device, Reduce_half_t_16) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_device<
|
||||
cutlass::half_t,
|
||||
16
|
||||
>().run();
|
||||
}
|
||||
|
||||
TEST(Reduce_thread_device, Reduce_half_t_31) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_device<
|
||||
cutlass::half_t,
|
||||
31
|
||||
>().run();
|
||||
}
|
||||
|
||||
|
||||
TEST(Reduce_thread_host, Reduce_float_1) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_host<
|
||||
float,
|
||||
1
|
||||
>().run();
|
||||
}
|
||||
|
||||
TEST(Reduce_thread_host, Reduce_float_16) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_host<
|
||||
float,
|
||||
16
|
||||
>().run();
|
||||
|
||||
}
|
||||
|
||||
TEST(Reduce_thread_host, Reduce_half_t_1) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_host<
|
||||
cutlass::half_t,
|
||||
1
|
||||
>().run();
|
||||
}
|
||||
|
||||
TEST(Reduce_thread_host, Reduce_half_t_16) {
|
||||
|
||||
test::reduction::thread::Testbed_reduce_host<
|
||||
cutlass::half_t,
|
||||
16
|
||||
>().run();
|
||||
}
|
||||
|
||||
/////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
@@ -0,0 +1,236 @@
|
||||
/***************************************************************************************************
|
||||
* Copyright (c) 2017-2019, 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 TOR (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 Unit tests for thread-level Reduction
|
||||
*/
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "cutlass/reduction/thread/reduce.h"
|
||||
|
||||
#include "cutlass/layout/vector.h"
|
||||
#include "cutlass/util/host_tensor.h"
|
||||
#include "cutlass/util/tensor_view_io.h"
|
||||
|
||||
#include "cutlass/util/reference/host/tensor_copy.h"
|
||||
#include "cutlass/util/reference/host/tensor_fill.h"
|
||||
#include "cutlass/util/reference/host/tensor_compare.h"
|
||||
|
||||
namespace test {
|
||||
namespace reduction {
|
||||
namespace thread {
|
||||
|
||||
/////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
/// Structure to compute the reduction
|
||||
template <
|
||||
/// Data type of elements
|
||||
typename Element,
|
||||
/// Number of elements
|
||||
int N
|
||||
>
|
||||
struct Testbed_reduce_host {
|
||||
|
||||
/// Thread-level reduction operator
|
||||
using Reduce = cutlass::reduction::thread::Reduce<
|
||||
cutlass::plus<Element>,
|
||||
cutlass::Array<Element, N>
|
||||
>;
|
||||
|
||||
//
|
||||
// Data members
|
||||
//
|
||||
|
||||
cutlass::Array<Element, N> tensor_in;
|
||||
cutlass::Array<Element, 1> reduced_tensor_computed;
|
||||
cutlass::Array<Element, 1> reduced_tensor_reference;
|
||||
|
||||
//
|
||||
// Methods
|
||||
//
|
||||
|
||||
/// Allocates workspace in device memory
|
||||
Testbed_reduce_host() {
|
||||
tensor_in.clear();
|
||||
reduced_tensor_computed.clear();
|
||||
reduced_tensor_reference.clear();
|
||||
}
|
||||
|
||||
/// Runs the test
|
||||
bool run() {
|
||||
|
||||
//
|
||||
// initialize memory
|
||||
//
|
||||
|
||||
for(int i = 0; i < N; i++)
|
||||
tensor_in.at(i) = Element(i);
|
||||
|
||||
|
||||
Reduce reduce;
|
||||
|
||||
cutlass::Array<Element, 1> *out_ptr = &reduced_tensor_computed;
|
||||
out_ptr[0] = reduce(tensor_in);
|
||||
|
||||
//
|
||||
// Reference implementation
|
||||
//
|
||||
Element e(0);
|
||||
for (int i = 0; i < N; i++)
|
||||
e = e + Element(i);
|
||||
|
||||
reduced_tensor_reference.at(0) = e;
|
||||
|
||||
//
|
||||
// Verify equivalence
|
||||
//
|
||||
|
||||
// compare
|
||||
bool passed = reduced_tensor_reference[0] == reduced_tensor_computed[0];
|
||||
|
||||
EXPECT_TRUE(passed)
|
||||
<< "Expected = " << float(reduced_tensor_reference.at(0)) << "\n\n"
|
||||
<< "Actual = " << float(reduced_tensor_computed.at(0)) << "\n\n"
|
||||
<< std::endl;
|
||||
|
||||
return passed;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
/////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
/// Thread-level reduction kernel
|
||||
template <typename Element, int N>
|
||||
__global__ void kernel_reduce(Element const *array_in, Element *result) {
|
||||
|
||||
/// Thread-level reduction operator
|
||||
using Reduce = cutlass::reduction::thread::Reduce<
|
||||
cutlass::plus<Element>,
|
||||
cutlass::Array<Element, N>
|
||||
>;
|
||||
|
||||
Reduce reduce;
|
||||
|
||||
auto ptr_in = reinterpret_cast<cutlass::Array<Element , N> const *>(array_in);
|
||||
auto result_ptr = reinterpret_cast<cutlass::Array<Element , 1> *>(result);
|
||||
auto in = *ptr_in;
|
||||
result_ptr[0] = reduce(in);
|
||||
}
|
||||
|
||||
|
||||
/// Structure to compute the reduction
|
||||
template <
|
||||
/// Data type of elements
|
||||
typename Element,
|
||||
/// Number of elements
|
||||
int N
|
||||
>
|
||||
struct Testbed_reduce_device {
|
||||
|
||||
using Layout = cutlass::layout::PackedVectorLayout;
|
||||
|
||||
//
|
||||
// Data members
|
||||
//
|
||||
|
||||
cutlass::HostTensor<Element, Layout> tensor_in;
|
||||
cutlass::HostTensor<Element, Layout> reduced_tensor_computed;
|
||||
cutlass::HostTensor<Element, Layout> reduced_tensor_reference;
|
||||
|
||||
//
|
||||
// Methods
|
||||
//
|
||||
|
||||
/// Allocates workspace in device memory
|
||||
Testbed_reduce_device() {
|
||||
|
||||
tensor_in.reset(cutlass::make_Coord(N), true);
|
||||
reduced_tensor_computed.reset(cutlass::make_Coord(1), true);
|
||||
reduced_tensor_reference.reset(cutlass::make_Coord(1), true);
|
||||
}
|
||||
|
||||
|
||||
/// Runs the test
|
||||
bool run() {
|
||||
|
||||
//
|
||||
// initialize memory
|
||||
//
|
||||
|
||||
cutlass::reference::host::TensorFill(
|
||||
tensor_in.host_view(),
|
||||
Element(1)
|
||||
);
|
||||
|
||||
cutlass::reference::host::TensorFill(
|
||||
reduced_tensor_computed.host_view(),
|
||||
Element(0)
|
||||
);
|
||||
|
||||
cutlass::reference::host::TensorFill(
|
||||
reduced_tensor_reference.host_view(),
|
||||
Element(N)
|
||||
);
|
||||
|
||||
tensor_in.sync_device();
|
||||
reduced_tensor_computed.sync_device();
|
||||
reduced_tensor_reference.sync_device();
|
||||
|
||||
/// call the kernel
|
||||
kernel_reduce<Element, N><<< dim3(1, 1), dim3(1, 1, 1) >>> (
|
||||
tensor_in.device_data(),
|
||||
reduced_tensor_computed.device_data()
|
||||
);
|
||||
|
||||
// verify no errors
|
||||
cudaError_t result = cudaDeviceSynchronize();
|
||||
|
||||
EXPECT_EQ(result, cudaSuccess) << "CUDA ERROR: " << cudaGetErrorString(result);
|
||||
if (result != cudaSuccess) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Copy back results
|
||||
reduced_tensor_computed.sync_host();
|
||||
|
||||
// Verify equivalence
|
||||
bool passed = cutlass::reference::host::TensorEquals(
|
||||
reduced_tensor_computed.host_view(),
|
||||
reduced_tensor_reference.host_view()
|
||||
);
|
||||
|
||||
EXPECT_TRUE(passed)
|
||||
<< "Expected = " << reduced_tensor_reference.host_view() << "\n\n"
|
||||
<< "Actual = " << reduced_tensor_computed.host_view() << "\n\n"
|
||||
<< std::endl;
|
||||
|
||||
return passed;
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace thread
|
||||
} // namespace reduction
|
||||
} // namespace test
|
||||
Reference in New Issue
Block a user