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Exploring Memory Access Patterns for Graph Processing Accelerators

dc.contributor.authorDann, Jonas
dc.contributor.authorRitter, Daniel
dc.contributor.authorFröning, Holger
dc.contributor.editorKai-Uwe Sattler
dc.contributor.editorMelanie Herschel
dc.contributor.editorWolfgang Lehner
dc.date.accessioned2021-03-16T07:57:12Z
dc.date.available2021-03-16T07:57:12Z
dc.date.issued2021
dc.description.abstractRecent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases and data science platforms. FPGAs as accelerators for graph processing with a customizable memory hierarchy promise solving performance problems caused by inherent irregular memory access patterns on traditional hardware (e.g., CPU). However, developing such hardware accelerators is yet time-consuming and difficult and benchmarking is non-standardized, hindering comprehension of the impact of memory access pattern changes and systematic engineering of graph processing accelerators. In this work, we propose a simulation environment for the analysis of graph processing accelerators based on simulating their memory access patterns. Further, we evaluate our approach on two state-of-the-art FPGA graph processing accelerators and show reproducibility, comparablity, as well as the shortened development process by an example. Not implementing the cycle-accurate internal data flow on accelerator hardware like FPGAs significantly reduces the implementation time, increases the benchmark parameter transparency, and allows comparison of graph processing approaches.en
dc.identifier.doi10.18420/btw2021-05
dc.identifier.isbn978-3-88579-705-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/35810
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-311
dc.subjectDRAM
dc.subjectFPGA
dc.subjectGraph processing
dc.subjectIrregular memory access patterns
dc.subjectSimulation
dc.titleExploring Memory Access Patterns for Graph Processing Acceleratorsen
gi.citation.endPage122
gi.citation.startPage101
gi.conference.date13.-17. September 2021
gi.conference.locationDresden
gi.conference.sessiontitleDatabase Technology

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