A unified framework for optimizing communication in data-parallel programs

doi:10.1109/71.508249

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A unified framework for optimizing communication in data-parallel programs

1996-07-01

PRE

Manish Gupta *

Edith Schonberg

Harini Srinivasan

DOI：10.1109/71.508249

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Abstract

En 中文

This paper presents a framework, based on global array data-flow analysis, to reduce communication costs in a program being compiled for a distributed memory machine. We introduce available section descriptor, a novel representation of communication involving array sections. This representation allows us to apply techniques for partial redundancy elimination to obtain powerful communication optimizations. With a single framework, we are able to capture optimizations like 1) vectorizing communication, 2) eliminating communication that is redundant on any control flow path, 3) reducing the amount of data being communicated, 4) reducing the number-of processors to which data must be communicated, and (5) moving communication earlier to hide latency, and to subsume previous communication. We show that the bidirectional problem of eliminating partial redundancies can be decomposed into simpler unidirectional problems even in the context of an array section representation, which makes the analysis procedure more efficient. We present results from a preliminary implementation of this framework, which are extremely encouraging, and demonstrate the effectiveness of this analysis in improving the performance of programs.

Keywords:

array section descriptors

communication optimizations

data availability

data-flow analysis

data-parallelism

High Performance Fortran

partial redundancy elimination

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