A data-parallel extension to Ruby for GPGPU: toward a framework for implementing domain-specific optimizations

Authors:
Hidehiko Masuhara;Yusuke Nishiguchi
Affiliations:
University of Tokyo, JST/CREST;University of Tokyo
Venue:
Proceedings of the 9th ECOOP Workshop on Reflection, AOP, and Meta-Data for Software Evolution
Year:
2012

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Abstract

We propose Ikra, a data-parallel extension to Ruby for general-purpose computing on graphical processing unit (GPGPU). Our approach is to provide a special array class with higher-order methods for describing computation on a GPU. With a static type inference system that identifies code fragments that shall be executed on a GPU and with a skeleton-based compiler that generates CUDA code, we aim at separating application logic and parallelization and optimizations. The paper presents the design of Ikra and an overview of its implementation along with preliminary performance evaluation.