Publication
LLVM-HPC 2018
Conference paper

OP2-clang: A source-to-source translator using clang/LLVM LibTooling

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Abstract

Domain Specific Languages or Active Library frameworks have recently emerged as an important method for gaining performance portability, where an application can be efficiently executed on a wide range of HPC architectures without significant manual modifications. Embedded DSLs such as OP2, provides an API embedded in general purpose languages such as C/C++/Fortran. They rely on source-to-source translation and code refactorization to translate the higher-level API calls to platform specific parallel implementations. OP2 targets the solution of unstructured-mesh computations, where it can generate a variety of parallel implementations for execution on architectures such as CPUs, GPUs, distributed memory clusters and heterogeneous processors making use of a wide range of platform specific optimizations. Compiler tool-chains supporting source-to-source translation of code written in mainstream languages currently lack the capabilities to carry out such wide-ranging code transformations. Clang/LLVM's ∗The following names are subject to trademark: LLVM™, CLANG™, NVIDIA™, P100™, CUDA™, INTEL™, Tooling library (LibTooling) has long been touted as having such capabilities but have only demonstrated its use in simple source refactoring tasks. In this paper we introduce OP2-Clang, a source-to-source translator based on LibTooling, for OP2's C/C++ API, capable of generating target parallel code based on SIMD, OpenMP, CUDA and their combinations with MPI. OP2-Clang is designed to significantly reduce maintenance, particularly making it easy to be extended to generate new parallelizations and optimizations for hardware platforms. In this research, we demonstrate its capabilities including (1) the use of LibTooling's AST matchers together with a simple strategy that use parallelization templates or skeletons to significantly reduce the complexity of generating radically different and transformed target code and (2) chart the challenges and solution to generating optimized parallelizations for OpenMP, SIMD and CUDA. Results indicate that OP2-Clang produces near-identical parallel code to that of OP2's current source-to-source translator. We believe that the lessons learnt in OP2-Clang can be readily applied to developing other similar source-to-source translators, particularly for DSLs.

Date

Publication

LLVM-HPC 2018

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