Programmer’s guide

This document provides insight into the library source code organization, design implementation details, helpful information for new development, and testing and benchmarking details.

Library source code organization

The rocWMMA code is split into four major parts:

• The library directory contains the library source code.

• The samples directory contains real-world use-cases of the rocWMMA API.

• The test directory contains validation tests for rocWMMA API.

• Infrastructure

library directory

The library directory contains the following include files:

• library/include/rocwmma/: C++ include files for the rocWMMA API. These files also contain Doxygen comments that document the API.

• library/include/internal: Internal include files for:

  • Type support

  • Input and output configuration, shapes and traits

  • Layout

  • Mapping Utility

  • Cross-lane operation utility

  • Vector blend utility

  • Packing and unpacking

  • Conversion and broadcasting

  • Load and store

  • Matrix multiply-accumulate

  • Cooperative load and store

  • Threadblock synchronization

  • Utility code

samples directory

The samples directory contains the sample codes for the following use cases:

• samples/hipRTC_gemm.cpp: For calling simple General Matrix Multiply (GEMM) algorithm demonstration without LDS memory usage and no transpose, from within the hipRTC environment

• samples/simple_sgemv.cpp: For calling simple matrix multiply-accumulate with a vector demonstration, without LDS and no transpose for single-precision floating point types

• samples/simple_dgemv.cpp: For calling simple matrix multiply-accumulate with a vector demonstration, without LDS and no transpose for double-precision floating point types

• samples/simple_sgemm.cpp: For calling simple GEMM algorithm demonstration without LDS memory usage and no transpose for single-precision floating point types

• samples/simple_dgemm.cpp: For calling simple GEMM algorithm demonstration without LDS memory usage and no transpose for double-precision floating point types

• samples/simple_hgemm.cpp: For calling simple GEMM algorithm demonstration without LDS memory usage and no transpose for half-precision floating point types

• samples/perf_sgemm.cpp: For calling the best performing multi-block GEMM algorithm demonstration with LDS memory, macro tile collaboration, data reuse and optimized pipeline for single-precision floating point types

• samples/perf_dgemm.cpp: For calling the best performing multi-block GEMM algorithm demonstration with LDS memory, macro tile collaboration, data reuse and optimized pipeline for double-precision floating point types

• samples/perf_hgemm.cpp: For calling the best performant multi-block GEMM algorithm demonstration with LDS memory, macro tile collaboration, data reuse and optimized pipeline for half-precision floating point types

• samples/simple_dlrm.cpp: For calling simple Deep Learning Recommendation Model (DLRM) for machine learning

• samples/common.hpp: Common code used by all the above rocWMMA samples files

test directory

The test directory contains the test codes for testing the following functionalities:

• test/bin: To generate benchmark plots from the gtest output dumps of rocWMMA’s benchmark tests.

• test/dlrm: For various strategies of DLRM application. This test is used to validate DLRM functions using rocWMMA API.

• test/gemm: For various strategies of GEMM application. This test is used to validate and benchmark GEMM functions using rocWMMA API.

• test/unit: For testing the basic functional units of rocWMMA library.

Infrastructure

• CMake is used to build and package rocWMMA. There are CMakeLists.txt files throughout the code.

• Doxygen/Breathe/Sphinx/ReadTheDocs are used to produce documentation. The API documentation is generated using:

  • Doxygen comments in include files in the directory library/include

  • files in the directory docs/source.

• Jenkins is used to automate Continuous Integration (CI) testing.

• clang-format is used to format C++ code.