Title :
A decomposition advisory system for heterogeneous data-parallel processing
Author :
Crandall, Phyllis E. ; Quinn, Michael J.
Author_Institution :
Dept. of Comput. Sci., Oregon State Univ., Corvallis, OR, USA
Abstract :
Networked computing has become a popular method for using parallelism to solve a variety of computationally intense problems. However, high communication costs and processor heterogeneity may limit performance unless the problem space is carefully partitioned. We propose a decomposition advisory system that is designed to help choose the best data partitioning strategy. The goal of this research is to determine the partitioning scheme(s) expected to yield the best performance for a particular data-parallel problem with known regular communication patterns on a collection of heterogeneous processors. Given information about the problem space and the network, the system provides a ranking of standard partitioning methods
Keywords :
distributed memory systems; expert systems; multiprocessing programs; open systems; parallel programming; program compilers; resource allocation; telecommunication network management; computationally intense problems; data partitioning strategy; decomposition advisory system; heterogeneous data-parallel processing; high performance computing; networked computing; problem space; Computer networks; Computer science; Concurrent computing; Costs; High performance computing; Load management; Parallel processing; Programming profession; Runtime; Supercomputers;
Conference_Titel :
High Performance Distributed Computing, 1994., Proceedings of the Third IEEE International Symposium on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-6395-2
DOI :
10.1109/HPDC.1994.340253
