How Portable is Nested Data Parallelism?

Manuel M. T. Chakravarty and Gabriele Keller

In W. Cheng and A. S. M. Sajeev, editors, Proceedings of 6th Annual Australasian Conference on Parallel And Real-Time Systems (PART '99) , Springer-Verlag, 1999.

Abstract
Research on the high-performance implementation of nested data parallelism has, over time, covered a wide range of architectures. Scalar and vector processors as well as shared-memory and distributed memory machines were targeted. We are currently investigating methods to integrate this technology into a single portable compiler back-end. Essential to our approach are two program transformations, flattening and calculational fusion, which even out irregular parallelism and increase locality of reference, respectively. We generate C code that makes use of a portable, light-weight, collective-communication library. First experiments on scalar, vector, and distributed-memory machines support the feasibility of the approach.

PostScript version (14 pages).

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