The 7th International Conference on Next Generation Computing 2021 (2021.11)바로가기
페이지
pp.178-181
저자
Daegun Yoon, Sangyoon Oh
언어
영어(ENG)
URL
https://www.earticle.net/Article/A448039
원문정보
초록
영어
Breadth-first search (BFS) is one of the most used graph kernels, and substantially affects the overall performance when processing various graphs. Since graph data are frequently used in real life for example road networks in navigation systems, high performance graph processing becomes more critical. In this study, we aim to process BFS algorithm efficiently on road network data. We propose BARON, a BFS algorithm that copes with road networks. To accelerate graph traversal, BARON reduce the occurrence of branch and memory divergences by exploiting warp-cooperative work sharing and atomic operations. With this design approach, BARON outperforms the other BFS kernels of state-of-the-art graph processing frameworks executed stably on the latest GPU architectures. For various graphs, BARON yields speedups of up to 2.88 and 5.43 over Gunrock and CuSha, respectively.
목차
Abstract I. INTRODUCTION II. RELATED WORK III. BARON: BFS ALGORITHM FOR ROAD NETWORKS IV. EVALUATION A. Implementation and Hardware Specifications B. Methodology and Graph Benchmarks C. BFS Performance Comparison V. CONCLUSION ACKNOWLEDGMENT REFERENCES
키워드
breadth-first searchgraphroad networkgraphics processing units
저자
Daegun Yoon [ dept. of Artificial Intelligence Ajou University ]
Sangyoon Oh [ dept. of Artificial Intelligence Ajou University ]