Gunrock: a high-performance graph processing library on the GPU
Abstract
For large-scale graph analytics on the GPU, the irregularity of data access and control flow and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system, uses a high-level bulk-synchronous abstraction with traversal and computation steps, designed specifically for the GPU. Gunrock couples high performance with a high-level programming model that allows programmers to quickly develop new graph primitives with less than 300 lines of code. We evaluate Gunrock on five graph primitives and show that Gunrock has at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 24, 2015
- Source ID
- 10.1145/2858788.2688538
Entities
People
- Andrew D Davidson
- Andy Riffel
- John D. Owens
- Yangzihao Wang
- Yuduo Wu
- Yuechao Pan
Organizations
- Defense Advanced Research Projects Agency
- National Science Foundation
- University of California, Davis