Distributed Memory Compiler Methods for Irregular Problems - Data Copy Reuse and Runtime Partitioning
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 three dimensional unstructured Euler solve run on an iPSC/860 to demonstrate the usefulness of our methods.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1991
- Accession Number
- ADA242368
Entities
People
- Dimitri Mavriplis
- Joel Saltz
- Raja Das
- Ravi Ponnusamy