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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

210 lines
6.4 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (C) 2022-2025 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
*******************************************************************************/
#pragma once
#include <cstddef>
#include <map>
#include <memory>
#include <optional>
#include <shared_mutex>
#include <string>
#include <tuple>
#include <vector>
#include <tensilelitehost/export.h>
#include <Tensile/SolutionLibrary_fwd.hpp>
#include <Tensile/Tensile_fwd.hpp>
#include <Tensile/KernelArguments.hpp>
#include <Tensile/geom.hpp>
/**
* \mainpage
*
* Tensile is a tool for creating a library of tensor contractions, including
* matrix multiplications in a benchmark-driven manner.
*
* The host library contains classes and functions for selecting one or more
* kernels to launch to solve a particular problem, and then launching those
* kernels. Kernels are selected based on the performance on a particular GPU
* (from the benchmark runs) as well as the limitations and applicability of
* the kernels to particular problem sizes.
*
* Design goals for the host library include:
* - A library that requires no generated code on the host
* - Kernel selection configured via a file
* - No recompilation needed to enable a different set of kernels.
* - Kernel selection & determination of kernel launches decoupled from host
* runtime language
* - Eliminate as much of the Hip and OpenCL-specific code as possible
* - Support future work including implicit GEMMs
* - Use modern C++
* - Eliminate the need for client code to call intricately named functions
* such as `tensile_Cijk_Ailk_Bljk_SB()`.
*/
/**
* \addtogroup Tensile
* @{
*/
/**
* @brief Primary namespace for Tensile host code.
*/
namespace TensileLite
{
/**
* \ingroup Tensile
* \defgroup Problem Problem Definition
*
* @brief Classes for defining problems
*/
/**
* \ingroup Problem
* Base Problem class. A Problem object generically describes a problem to
* be solved including the type of problem, all sizes and strides, but not
* including actual pointers to data.
*/
class TENSILELITEHOST_EXPORT Problem
{
public:
virtual ~Problem();
virtual std::string description() const = 0;
};
/**
* \ingroup Problem
* Base class for problem inputs. This stores the actual pointers to the
* data.
*/
class TENSILELITEHOST_EXPORT ProblemInputs
{
public:
virtual ~ProblemInputs();
};
/**
* \ingroup Tensile
* \defgroup Launching Kernel Launching
*/
/**
* \ingroup Launching
* Describes a single kernel invocation including kernel name, launch
* bounds, and arguments.
*/
struct TENSILELITEHOST_EXPORT KernelInvocation
{
public:
std::string kernelName;
std::string codeObjectFile; //Code object file kernel is located in
bool isSingleCall = false;
dim3 clusterDim{1, 1, 1};
dim3 workGroupSize;
dim3 numWorkGroups;
dim3 numWorkItems;
size_t sharedMemBytes = 0;
KernelArguments args;
};
/**
* \ingroup Tensile
* \defgroup Hardware Hardware Description Classes
*/
/**
* \ingroup Hardware
* Abstract base class for describing hardware capabilities and properties.
*/
class TENSILELITEHOST_EXPORT Hardware
{
public:
Hardware();
virtual ~Hardware();
virtual size_t id() const = 0;
virtual std::string description() const = 0;
virtual std::string archName() const = 0;
virtual std::optional<int> pciChipId() const { return std::nullopt; }
};
/**
* \ingroup Solution
* Generally encapsulates a single kernel or set of kernels that can be
* used to solve a particular problem.
*/
class TENSILELITEHOST_EXPORT Solution
{
public:
virtual ~Solution();
virtual std::string name() const = 0;
virtual std::string description() const = 0;
virtual bool isFallbackForHW(Hardware const&) const = 0;
};
/**
* \ingroup Launching
* Base class for objects capable of launching kernels based on
* KernelArguments objects.
*/
class TENSILELITEHOST_EXPORT SolutionAdapter
{
public:
virtual ~SolutionAdapter();
virtual std::string name() const = 0;
};
/**
* Interface for deserializing a library file.
*/
enum class LazyLoadingInit;
TENSILELITEHOST_EXPORT std::map<int, std::string> LoadLibraryMapping(std::string const& filename);
template <typename MyProblem, typename MySolution = typename MyProblem::Solution>
TENSILELITEHOST_EXPORT std::shared_ptr<SolutionLibrary<MyProblem, MySolution>>
LoadLibraryFile(std::string const& filename);
template <typename MyProblem, typename MySolution = typename MyProblem::Solution>
TENSILELITEHOST_EXPORT std::shared_ptr<SolutionLibrary<MyProblem, MySolution>>
LoadLibraryFilePreload(std::string const& filename,
const std::vector<LazyLoadingInit>& preload);
template <typename MyProblem, typename MySolution = typename MyProblem::Solution>
std::shared_ptr<SolutionLibrary<MyProblem, MySolution>>
LoadLibraryData(std::vector<uint8_t> const& data);
} // namespace TensileLite
/** @} */