cutlass/tools/profiler/src/gemm_operation_profiler.h
Andrew Kerr fb335f6a5f
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.
2019-11-19 16:55:34 -08:00

198 lines
5.9 KiB
C++

/***************************************************************************************************
* 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
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**************************************************************************************************/
/* \file
\brief Defines a math function
*/
#pragma once
#include <vector>
#include <string>
#include <memory>
#include <unordered_map>
// CUTLASS Library includes
#include "cutlass/library/library.h"
#include "cutlass/library/manifest.h"
// Profiler includes
#include "options.h"
#include "device_context.h"
#include "operation_profiler.h"
#include "performance_result.h"
#include "problem_space.h"
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace profiler {
/////////////////////////////////////////////////////////////////////////////////////////////////
/// Abstract base class for each math function
class GemmOperationProfiler : public OperationProfiler {
public:
/// Problem structure obtained from problem space
struct GemmProblem {
int64_t m;
int64_t n;
int64_t k;
int64_t lda;
int64_t ldb;
int64_t ldc;
std::vector<uint8_t> alpha;
std::vector<uint8_t> beta;
int64_t split_k_slices;
int64_t batch_count;
//
// Methods
//
GemmProblem():
m(16), n(16), k(16), lda(0), ldb(0), ldc(0), split_k_slices(1), batch_count(1) { }
};
/// Workspace used
struct GemmWorkspace {
DeviceAllocation *A;
DeviceAllocation *B;
DeviceAllocation *C;
DeviceAllocation *Computed;
DeviceAllocation *Reference;
library::GemmConfiguration configuration;
library::GemmArguments arguments;
/// Buffer used for the operation's host workspace
std::vector<uint8_t> host_workspace;
/// Buffer used for the operations' device workspace
DeviceAllocation device_workspace;
//
// Methods
//
GemmWorkspace():
A(nullptr), B(nullptr), C(nullptr), Computed(nullptr), Reference(nullptr) { }
};
protected:
//
// Data members
//
/// GEMM problem obtained from problem space
GemmProblem problem_;
/// Device memory allocations
GemmWorkspace gemm_workspace_;
public:
//
// Methods
//
/// Ctor
GemmOperationProfiler();
/// Destructor
virtual ~GemmOperationProfiler();
/// Prints usage statement for the math function
virtual void print_usage(std::ostream &out) const;
/// Prints examples
virtual void print_examples(std::ostream &out) const;
/// Extracts the problem dimensions
virtual Status initialize_configuration(
Options const &options,
PerformanceReport &report,
DeviceContext &device_context,
library::Operation const *operation,
ProblemSpace const &problem_space,
ProblemSpace::Problem const &problem);
/// Initializes workspace
virtual Status initialize_workspace(
Options const &options,
PerformanceReport &report,
DeviceContext &device_context,
library::Operation const *operation,
ProblemSpace const &problem_space,
ProblemSpace::Problem const &problem);
/// Verifies CUTLASS against references
virtual bool verify_cutlass(
Options const &options,
PerformanceReport &report,
DeviceContext &device_context,
library::Operation const *operation,
ProblemSpace const &problem_space,
ProblemSpace::Problem const &problem);
/// Measures performance results
virtual bool profile(
Options const &options,
PerformanceReport &report,
DeviceContext &device_context,
library::Operation const *operation,
ProblemSpace const &problem_space,
ProblemSpace::Problem const &problem);
protected:
/// Initializes the performance result
void initialize_result_(
PerformanceResult &result,
Options const &options,
library::GemmDescription const &operation_desc,
ProblemSpace const &problem_space);
/// Verifies CUTLASS against references
bool verify_with_cublas_(
Options const &options,
PerformanceReport &report,
DeviceContext &device_context,
library::Operation const *operation,
ProblemSpace const &problem_space,
ProblemSpace::Problem const &problem);
};
/////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace profiler
} // namespace cutlass
/////////////////////////////////////////////////////////////////////////////////////////////////