GraphAttack
Abstract
Graph structures are a natural representation of important and pervasive data. While graph applications have significant parallelism, their characteristic pointer indirect loads to neighbor data hinder scalability to large datasets on multicore systems. A scalable and efficient system must tolerate latency while leveraging data parallelism across millions of vertices. Modern Out-of-Order (OoO) cores inherently tolerate a fraction of long latencies, but become clogged when running severely memory-bound applications. Combined with large power/area footprints, this limits their parallel scaling potential and, consequently, the gains that existing software frameworks can achieve. Conversely, accelerator and memory hierarchy designs provide performant hardware specializations, but cannot support diverse application demands.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 03, 2021
- Source ID
- 10.1145/3469846
Entities
People
- Aninda Manocha
- Esin Tureci
- Juan L. Aragon
- Margaret Martonosi
- Opeoluwa Matthews
- Tyler Sorensen
Organizations
- Agencia Estatal de Investigación
- Defense Advanced Research Projects Agency
- Princeton University
- University of California, Santa Cruz
- University of Murcia