{"title":"Dynamic-ACTS - 面向 HBM FPGA 的动态图形分析加速器","authors":"Oluwole Jaiyeoba, Kevin Skadron","doi":"10.1145/3662002","DOIUrl":null,"url":null,"abstract":"<p>Graph processing frameworks suffer performance degradation from under-utilization of available memory bandwidth, because graph traversal often exhibits poor locality. A prior work, ACTS [24], accelerates graph processing with FPGAs and High Bandwidth Memory (HBM). ACTS achieves locality by partitioning vertex-update messages (based on destination vertex IDs) generated online after active edges have been processed. This work introduces Dynamic-ACTS which builds on ideas in ACTS to support dynamic graphs. The key innovation is to use a hash table to find the edges to be updated. Compared to Gunrock, a GPU graph engine, Dynamic-ACTS achieves a geometric mean speedup of 1.5X, with a maximum speedup of 4.6X. Compared to GraphLily, an FPGA-HBM graph engine, Dynamic-ACTS achieves a geometric speedup of 3.6X, with a maximum speedup of 16.5X. Our results also showed a geometric mean power reduction of 50% and a mean reduction of energy-delay product of 88% over Gunrock. Compared to GraSU, an FPGA graph updating engine, Dynamic-ACTS achieves an average speedup of 15X.</p>","PeriodicalId":49248,"journal":{"name":"ACM Transactions on Reconfigurable Technology and Systems","volume":"12 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic-ACTS - A Dynamic Graph Analytics Accelerator For HBM-Enabled FPGAs\",\"authors\":\"Oluwole Jaiyeoba, Kevin Skadron\",\"doi\":\"10.1145/3662002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Graph processing frameworks suffer performance degradation from under-utilization of available memory bandwidth, because graph traversal often exhibits poor locality. A prior work, ACTS [24], accelerates graph processing with FPGAs and High Bandwidth Memory (HBM). ACTS achieves locality by partitioning vertex-update messages (based on destination vertex IDs) generated online after active edges have been processed. This work introduces Dynamic-ACTS which builds on ideas in ACTS to support dynamic graphs. The key innovation is to use a hash table to find the edges to be updated. Compared to Gunrock, a GPU graph engine, Dynamic-ACTS achieves a geometric mean speedup of 1.5X, with a maximum speedup of 4.6X. Compared to GraphLily, an FPGA-HBM graph engine, Dynamic-ACTS achieves a geometric speedup of 3.6X, with a maximum speedup of 16.5X. Our results also showed a geometric mean power reduction of 50% and a mean reduction of energy-delay product of 88% over Gunrock. Compared to GraSU, an FPGA graph updating engine, Dynamic-ACTS achieves an average speedup of 15X.</p>\",\"PeriodicalId\":49248,\"journal\":{\"name\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3662002\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Reconfigurable Technology and Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3662002","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Dynamic-ACTS - A Dynamic Graph Analytics Accelerator For HBM-Enabled FPGAs
Graph processing frameworks suffer performance degradation from under-utilization of available memory bandwidth, because graph traversal often exhibits poor locality. A prior work, ACTS [24], accelerates graph processing with FPGAs and High Bandwidth Memory (HBM). ACTS achieves locality by partitioning vertex-update messages (based on destination vertex IDs) generated online after active edges have been processed. This work introduces Dynamic-ACTS which builds on ideas in ACTS to support dynamic graphs. The key innovation is to use a hash table to find the edges to be updated. Compared to Gunrock, a GPU graph engine, Dynamic-ACTS achieves a geometric mean speedup of 1.5X, with a maximum speedup of 4.6X. Compared to GraphLily, an FPGA-HBM graph engine, Dynamic-ACTS achieves a geometric speedup of 3.6X, with a maximum speedup of 16.5X. Our results also showed a geometric mean power reduction of 50% and a mean reduction of energy-delay product of 88% over Gunrock. Compared to GraSU, an FPGA graph updating engine, Dynamic-ACTS achieves an average speedup of 15X.
期刊介绍：
TRETS is the top journal focusing on research in, on, and with reconfigurable systems and on their underlying technology. The scope, rationale, and coverage by other journals are often limited to particular aspects of reconfigurable technology or reconfigurable systems. TRETS is a journal that covers reconfigurability in its own right.
Topics that would be appropriate for TRETS would include all levels of reconfigurable system abstractions and all aspects of reconfigurable technology including platforms, programming environments and application successes that support these systems for computing or other applications.
-The board and systems architectures of a reconfigurable platform.
-Programming environments of reconfigurable systems, especially those designed for use with reconfigurable systems that will lead to increased programmer productivity.
-Languages and compilers for reconfigurable systems.
-Logic synthesis and related tools, as they relate to reconfigurable systems.
-Applications on which success can be demonstrated.
The underlying technology from which reconfigurable systems are developed. (Currently this technology is that of FPGAs, but research on the nature and use of follow-on technologies is appropriate for TRETS.)
In considering whether a paper is suitable for TRETS, the foremost question should be whether reconfigurability has been essential to success. Topics such as architecture, programming languages, compilers, and environments, logic synthesis, and high performance applications are all suitable if the context is appropriate. For example, an architecture for an embedded application that happens to use FPGAs is not necessarily suitable for TRETS, but an architecture using FPGAs for which the reconfigurability of the FPGAs is an inherent part of the specifications (perhaps due to a need for re-use on multiple applications) would be appropriate for TRETS.
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