Affiliation:
1. SAP SE, Germany and Heidelberg University, Germany
2. SAP SE, Germany
3. Heidelberg University, Germany
Abstract
Recent advances in graph processing on FPGAs promise to alleviate performance bottlenecks with irregular memory access patterns. Such bottlenecks challenge performance for a growing number of important application areas like machine learning and data analytics. While FPGAs denote a promising solution through flexible memory hierarchies and massive parallelism, we argue that current graph processing accelerators either use the off-chip memory bandwidth inefficiently or do not scale well across memory channels.
In this work, we propose GraphScale, a scalable graph processing framework for FPGAs. GraphScale combines multi-channel memory with asynchronous graph processing (i. e., for fast convergence on results) and a compressed graph representation (i. e., for efficient usage of memory bandwidth and reduced memory footprint). GraphScale solves common graph problems like breadth-first search, PageRank, and weakly-connected components through modular user-defined functions, a novel two-dimensional partitioning scheme, and a high-performance two-level crossbar design. Additionally, we extend GraphScale to scale to modern high-bandwidth memory (HBM) and reduce partitioning overhead of large graphs with binary packing.
Publisher
Association for Computing Machinery (ACM)
Reference31 articles.
1. Junwhan Ahn Sungpack Hong Sungjoo Yoo Onur Mutlu and Kiyoung Choi. 2015. A Scalable Processing-in-memory Accelerator for Parallel Graph Processing. In ISCA. ACM 105–117. Junwhan Ahn Sungpack Hong Sungjoo Yoo Onur Mutlu and Kiyoung Choi. 2015. A Scalable Processing-in-memory Accelerator for Parallel Graph Processing. In ISCA. ACM 105–117.
2. Osama G. Attia Tyler Johnson Kevin Townsend Phillip H. Jones and Joseph Zambreno. 2014. CyGraph: A Reconfigurable Architecture for Parallel Breadth-First Search. In IPDPS. 228–235. Osama G. Attia Tyler Johnson Kevin Townsend Phillip H. Jones and Joseph Zambreno. 2014. CyGraph: A Reconfigurable Architecture for Parallel Breadth-First Search. In IPDPS. 228–235.
3. Vignesh Balaji and Brandon Lucia . 2018. When is Graph Reordering an Optimization? Studying the Effect of Lightweight Graph Reordering Across Applications and Input Graphs . In IISWC. IEEE Computer Society , 203–214. Vignesh Balaji and Brandon Lucia. 2018. When is Graph Reordering an Optimization? Studying the Effect of Lightweight Graph Reordering Across Applications and Input Graphs. In IISWC. IEEE Computer Society, 203–214.
4. Maciej Besta Emanuel Peter Robert Gerstenberger Marc Fischer Michal Podstawski Claude Barthels Gustavo Alonso and Torsten Hoefler. 2019. Demystifying Graph Databases: Analysis and Taxonomy of Data Organization System Designs and Graph Queries. CoRR abs/1910.09017(2019). Maciej Besta Emanuel Peter Robert Gerstenberger Marc Fischer Michal Podstawski Claude Barthels Gustavo Alonso and Torsten Hoefler. 2019. Demystifying Graph Databases: Analysis and Taxonomy of Data Organization System Designs and Graph Queries. CoRR abs/1910.09017(2019).