Title

Embedding Data Mappers with Distributed Memory Machine Compilers

Author(s)/Creator(s)

Ravi Ponnusamy, Syracuse UniversityFollow
Joel Saltz
Raja Das
Charles Koelbel
Alok Choudhary, Syracuse UniversityFollow

Document Type

Report

Date

4-1992

Keywords

data mappers

Language

English

Disciplines

Computer Sciences

Description/Abstract

In scalable multiprocessor systems, high performance demands that computational load be balanced evenly among processors and that interprocessor communication be limited as much as possible. Compilation techniques for achieving these goals have been explored extensively in recent years [3, 9, 11, 13, 17, 18]. This research has produced a variety of useful techniques, but most of it has assumed that the programmer specifies the distribution of large data structures among processor memories. A few projects have attempted to automatically derive data distributions for regular problems [12, 10, 8, 1]. In this paper, we study the more challenging problem of automatically choosing data distributions for irregular problems.

Additional Information

School of Computer and Information Science, Syracuse University, SU-CIS-92-06

Authors later published: Ponnusamy, R., Saltz, J., Das, R., Koelbel, C., & Choudhary, A. (1993). Embedding data mappers with distributed memory machine compilers. ACM SIGPLAN Notices, 28(1), 52-55. Association for Computing Machinery. doi:10.1145/156668.156687

Recommended Citation

Ponnusamy, Ravi; Saltz, Joel; Das, Raja; Koelbel, Charles; and Choudhary, Alok, "Embedding Data Mappers with Distributed Memory Machine Compilers" (1992). Electrical Engineering and Computer Science - Technical Reports. 175.
https://surface.syr.edu/eecs_techreports/175

Source

local