Abstract
In this paper, we advocate a composable approach to programming systems with Graphics Processing Units (GPU): programs are developed as compositions of generic, reusable patterns. Current GPU programming approaches either rely on low-level, monolithic code without patterns (CUDA and OpenCL), which achieves high performance at the cost of cumbersome and error-prone programming, or they improve the programmability by using pattern-based abstractions (e.g., Thrust) but pay a performance penalty due to inefficient implementations of pattern composition. We develop an API for GPUs based programming on C++ with STL-style patterns and its compiler-based implementation. Our API gives the application developers the native C++ means (views and actions) to specify precisely which pattern compositions should be automatically fused during code generation into a single efficient GPU kernel, thereby ensuring a high target performance. We implement our approach by extending the range-v3 library which is currently being developed for the forthcoming C++ standards. The composable programming in our approach is done exclusively in the standard C++14, with STL algorithms used as patterns which we re-implemented in parallel for GPU. Our compiler implementation is based on the LLVM and Clang frameworks, and we use advanced multi-stage programming techniques for aggressive runtime optimizations. We experimentally evaluate our approach using a set of benchmark applications and a real-world case study from the area of image processing. Our codes achieve performance competitive with CUDA monolithic implementations, and we outperform pattern-based codes written using Nvidia’s Thrust.
Original language | English |
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Title of host publication | PMAM'17 Proceedings of the 8th International Workshop on Programming Models and Applications for Multicores and Manycores |
Publisher | ACM |
Pages | 58-67 |
Number of pages | 10 |
ISBN (Print) | 978-1-4503-4883-6 |
DOIs | |
Publication status | Published - 4 Feb 2017 |
Event | 8th International Workshop on Programming Models and Applications for Multicores and Manycores - Austin, United States Duration: 4 Feb 2017 → 8 Feb 2017 https://ppopp17.sigplan.org/track/pmam-2017-papers |
Conference
Conference | 8th International Workshop on Programming Models and Applications for Multicores and Manycores |
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Abbreviated title | PMAM 2017 |
Country/Territory | United States |
City | Austin |
Period | 4/02/17 → 8/02/17 |
Internet address |