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Proceedings of the ACM Workshop on High Performance Graph Processing最新文献

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Session details: Full Papers Session 3 会议细节:论文全文会议3
Proceedings of the ACM Workshop on High Performance Graph Processing Pub Date : 2016-05-31 DOI: 10.1145/3260997
T. Suzumura
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引用次数: 0
Proceedings of the ACM Workshop on High Performance Graph Processing ACM高性能图形处理研讨会论文集
Proceedings of the ACM Workshop on High Performance Graph Processing Pub Date : 2016-05-31 DOI: 10.1145/2915516
T. Suzumura, D. García-Gasulla, Miyuru Dayarathna
{"title":"Proceedings of the ACM Workshop on High Performance Graph Processing","authors":"T. Suzumura, D. García-Gasulla, Miyuru Dayarathna","doi":"10.1145/2915516","DOIUrl":"https://doi.org/10.1145/2915516","url":null,"abstract":"It is our great pleasure to welcome you to the 2016 High Performance Graph Processing Workshop -- HPGP'16. This inaugural workshop of the HPGP workshop series is focused on multiple aspects of graph processing on high performance computing systems. The mission of the workshop is to serve as a platform for dissemination of cutting edge research conducted on high performance graph processing and identify new directions for future research and development. HPGP'16 provides researchers and practitioners a unique opportunity to share their perspectives with others interested in the various aspects of high performance graph processing. \u0000 \u0000The call for papers attracted submissions mainly from Asia and the United States. \u0000 \u0000We also encourage attendees to attend the keynote talk. This valuable and insightful talk can and will guide us to a better understanding of the future of high performance graph processing: \u0000Towards next-generation graph processing and management platform, Toyotaro Suzumura (who is currently at IBM T.J. Watson Research Center).","PeriodicalId":20568,"journal":{"name":"Proceedings of the ACM Workshop on High Performance Graph Processing","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74376712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
NUMA-aware Scalable Graph Traversal on SGI UV Systems 基于numa的SGI UV系统的可扩展图遍历
Proceedings of the ACM Workshop on High Performance Graph Processing Pub Date : 2016-05-31 DOI: 10.1145/2915516.2915522
Yuichiro Yasui, K. Fujisawa, E. L. Goh, John Baron, A. Sugiura, Takashi Uchiyama
{"title":"NUMA-aware Scalable Graph Traversal on SGI UV Systems","authors":"Yuichiro Yasui, K. Fujisawa, E. L. Goh, John Baron, A. Sugiura, Takashi Uchiyama","doi":"10.1145/2915516.2915522","DOIUrl":"https://doi.org/10.1145/2915516.2915522","url":null,"abstract":"Breadth-first search (BFS) is one of the most fundamental processing algorithms in graph theory. We previously presented a scalable BFS algorithm based on Beamer's direction-optimizing algorithm for non-uniform memory access (NUMA)-based systems, in which the NUMA architecture was carefully considered. This paper presents our new implementation that reduces remote memory access in a top-down direction of direction-optimizing algorithm. We also discuss numerical results obtained on the SGI UV 2000 and UV 300 systems, which are shared-memory supercomputers based on a cache coherent (cc)-NUMA architecture that can handle thousands of threads on a single operating system. Our implementation has achieved performance rates of 219 billion edges per second on a Kronecker graph with 234 vertices and 238 edges on a rack of an SGI UV 300 system with 1,152 threads. This result exceeds the fastest entry for a shared-memory system on the current Graph500 list presented in November 2015, which includes our previous implementation.","PeriodicalId":20568,"journal":{"name":"Proceedings of the ACM Workshop on High Performance Graph Processing","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90413134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
BLADYG: A Novel Block-Centric Framework for the Analysis of Large Dynamic Graphs 一个新的以块为中心的大型动态图分析框架
Proceedings of the ACM Workshop on High Performance Graph Processing Pub Date : 2016-05-31 DOI: 10.1145/2915516.2915525
Sabeur Aridhi, A. Montresor, Yannis Velegrakis
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引用次数: 8
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