Document Type
Report
Date
10-1991
Keywords
Distributed memory
Language
English
Disciplines
Computer Sciences
Description/Abstract
This paper outlines two methods which we believe will play an important role in any distributed memory compiler able to handle sparse and unstructured problems. We describe how to link runtime partitioners to distributed memory compilers. In our scheme, programmers can implicitly specify how data and loop iterations are to be distributed between processors. This insulates users from having to deal explicitly with potentially complex algorithms that carry out work and data partitioning. We also describe a viable mechanism for tracking and reusing copies of off-processor data. In many programs, several loops access the same off-processor memory locations. As long as it can be verified that the values assigned to off-processor memory locations remain unmodified, we show that we can effectively reuse stored off-processor data. We present experimental data from a 3-D unstructured Euler solver run on an iPSC/860 to demonstrate the usefulness of our methods.
Recommended Citation
Das, Raja; Ponnusamy, Ravi; Saltz, Joel; and Mavriplis, Dimitri, "Distributed Memory Compiler Methods for Irregular Problems -- Data Copy Reuse and Runtime Partitioning" (1991). Electrical Engineering and Computer Science - Technical Reports. 138.
https://surface.syr.edu/eecs_techreports/138
Source
local
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional Information
School of Computer and Information Science, Syracuse University, SU-CIS-91-36