fb335f6a5f
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.
124 lines
3.7 KiB
C++
124 lines
3.7 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/*! \file
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\brief AlignedBuffer is a container for trivially copyable elements suitable for use in
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unions and shared memory.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/array.h"
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namespace cutlass {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Modifies semantics of cutlass::Array<> to provide guaranteed alignment.
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template <
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typename T,
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int N,
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int Align = 16
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>
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struct AlignedBuffer {
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/// Internal storage type
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using Storage = uint8_t;
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/// Number of logical elements held in buffer
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static int const kCount = N;
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/// Alignment requirement in bytes
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static int const kAlign = Align;
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/// Number of storage elements
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static int const kBytes =
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(sizeof_bits<T>::value * N + 7) / 8;
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private:
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/// Internal storage
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alignas(Align) Storage storage[kBytes];
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public:
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//
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// C++ standard members
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//
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typedef T value_type;
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typedef size_t size_type;
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typedef ptrdiff_t difference_type;
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typedef value_type *pointer;
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typedef value_type const * const_pointer;
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using Array = Array<T, N>;
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using reference = typename Array::reference;
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using const_reference = typename Array::const_reference;
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public:
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CUTLASS_HOST_DEVICE
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pointer data() {
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return reinterpret_cast<pointer>(storage);
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}
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CUTLASS_HOST_DEVICE
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const_pointer data() const {
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return reinterpret_cast<pointer>(storage);
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}
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CUTLASS_HOST_DEVICE
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Storage * raw_data() {
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return storage;
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}
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CUTLASS_HOST_DEVICE
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Storage const * raw_data() const {
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return storage;
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}
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CUTLASS_HOST_DEVICE
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constexpr bool empty() const {
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return !kCount;
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}
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CUTLASS_HOST_DEVICE
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constexpr size_type size() const {
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return kCount;
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}
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CUTLASS_HOST_DEVICE
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constexpr size_type max_size() const {
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return kCount;
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace cutlass
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