Gluon: a communication-optimizing substrate for distributed heterogeneous graph analytics
Abstract
This paper introduces a new approach to building distributed-memory graph analytics systems that exploits heterogeneity in processor types (CPU and GPU), partitioning policies, and programming models. The key to this approach is Gluon, a communication-optimizing substrate.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 11, 2018
- Source ID
- 10.1145/3296979.3192404
Entities
People
- Alex Brooks
- Gurbinder Gill
- Hoang-vu Dang
- Keshav Pingali
- Loc Hoang
- Marc Snir
- Nikoli Dryden
- Roshan Dathathri
Organizations
- Defense Advanced Research Projects Agency
- National Science Foundation
- University of Illinois Urbana–Champaign
- University of Texas at Austin