The CMU Task Parallel Program Suite
Abstract
The idea of exploiting both task and data parallelism in programs is appealing. However, identifying realistic yet manageable example programs that can benefit from such a mix of task and data parallelism is a major problem for researchers. We address this problem by describing a suite of five applications from the domains of scientific, signal, and image processing that are of reasonable size, are representative of real codes, and can benefit from exploiting task and data parallelism. The suite includes fast Fourier transforms, narrowband tracking radar, multibaseline stereo imaging.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1994
- Accession Number
- ADA278951
Entities
People
- David O'hallaron
- Edward Segall
- Jon Webb
- Peter Dinda
- Thomas Gross
Organizations
- Carnegie Mellon University