Avoiding Communication in Successive Band Reduction
Abstract
The running time of an algorithm depends on both arithmetic and communication (i.e., data movement) costs, and the relative costs of communication are growing over time. In this work, we present sequential and distributed-memory parallel algorithms for tridiagonalizing full symmetric and symmetric band matrices that asymptotically reduce communication compared to previous approaches.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 18, 2015
- Source ID
- 10.1145/2686877
Entities
People
- Grey Ballard
- James Demmel
- Nicholas Knight
Organizations
- Defense Advanced Research Projects Agency
- Intel Corporation
- Lockheed Martin
- Microsoft
- National Instruments
- National Science Foundation
- Nokia
- Nvidia
- Oracle
- Samsung Group
- Sandia National Laboratories
- Semiconductor Research Corporation
- United States Department of Energy
- University of California, Berkeley