HAsP-Heterogeneous Associative Processing
Abstract
Heterogeneous processing (HP) is a technique intended for Grand Challenge and other high performance computing (HPC) problems and for bridging the gap between the theoretical potential of parallel processing and the current reality. In HP, we aim to match code and algorithms to best-suited architectures through techniques such as code profiling and analytic benchmarking. Associative computing (AsC) combines ideas from both associative memories and single instruction multiple data (SIMD) computers to look at new ways to use fine-grain parallel processors to achieve results beyond what is normally done by using spinoffs from sequential or multiple instruction multiple data (MIMD) processors. Heterogeneous associative processing (HAsP) is a generalization of the concepts of both HP and AsC. In HAsP, the AsC assumption of linking each datum with its own processor is generalized to assuming that each data file has its own dedicated computer. This paradigm maps onto all levels of granularity and can be easily emulated on most machines. The goal of HAsP is to allow the user to discuss the heterogeneous system aat the highest possible level and with the tightest possible synchronism. HAsP offers the potential of combining the simplifying programming approaches and algorithmic efficiencies of AsC with the performance of HP.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1992
- Accession Number
- ADA264990
Entities
People
- J. L. Potter
- R. F. Freund
Organizations
- Naval Command, Control and Ocean Surveillance Center