Moving Heterogeneous GPU Computing into the Mainstream with Directive-Based, High-Level Programming Models
GPU-based heterogeneous systems have emerged as promising alternatives for high-performance computing.
Recently, several directive-based GPU programming models have been proposed to provide better productivity than existing ones, such as CUDA and OpenCL.
- Directive-based models provide different levels of abstraction.
- Programming efforts required to conform to their models and optimize the performance also vary.
- Existing models do not scale well
- Understanding the differences in these new models will give valuable insights on the current issues and future research directions for the productive GPU computing
Information That GPU Directives Can Provide:
Seyong Lee and Jeffrey S. Vetter, Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing, SC12: ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis, November 2012
Seyong Lee and Jeffrey S. Vetter, Moving Heterogeneous GPU Computing into the Mainstream with Directive-Based, High-Level Programming Models (Position Paper), DOE Exascale Research Conference, April 2012