Abstract

This paper introduces the goals of the Portable, Scalable, Architecture Independent (PSI) Compiler Project for Data Parallel Languages at the University of Missouri-Rolla. A goal of this project is to produce a subcompiler for data parallel scientific programming languages such as HPF(High Performance Fortran) where the input grammar is translated to a three-address code intermediate language. Ultimately we plan to integrate our work into automated synthesis systems for scientific programming because we feel that it should not be necessary to learn complicated programming techniques to use multiprocessor computers or networks of computers effectively. This paper shows how to compile a data parallel language to an arbitrary multiprocessor topology or network of CPUs given the number of processors, length of vector registers, and total number of components in an array assuming a message passing, distributed memory paradigm of send and receive. We emphasize that this paradigm is not only amenable to machines such as the CM5 and NCube but to LAN and WAN connected architectures. We do automatic program partitioning and mapping to processing elements of a multiprocessor architecture or distributed network of machines. No programmer intervention is required, hence, no errors will be introduced through data decomposition.

Department(s)

Computer Science

Comments

This work was supported by the Natural Sciences and Engineering Council of Canada.

Keywords and Phrases

Data Parallelism; Supercompilers; Data Partitioning; Scientific Programming; Intermediate Languages

Report Number

CSC-93-01

Document Type

Technical Report

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 1993 University of Missouri--Rolla, All rights reserved.

Publication Date

07 Jan 1993

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