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Emerging hybrid accelerator architectures for high performance computing areoften suited for the use of a data-parallel programming model. Unfortunately,programmers of these architectures face a steep learning curve that frequentlyrequires learning a new language (e.g., OpenCL). Furthermore, the distributed(and frequently multi-level) nature of the memory organization of clusters ofthese machines provides an additional level of complexity. This paper presentspreliminary work examining how programming with a local orientation can beemployed to provide simpler access to accelerator architectures. Alocally-oriented programming model is especially useful for the solution ofalgorithms requiring the application of a stencil or convolution kernel. Inthis programming model, a programmer codes the algorithm by modifying only asingle array element (called the local element), but has read-only access to asmall sub-array surrounding the local element. We demonstrate how alocally-oriented programming model can be adopted as a language extension usingsource-to-source program transformations.

Locally-Oriented Programming: A Simple Programming Model for Stencil-Based Computations on Multi-Level Distributed Memory Architectures