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In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware

dc.contributor.authorBroneske, David
dc.contributor.authorDrewes, Anna
dc.contributor.authorGurumurthy, Bala
dc.contributor.authorHajjar, Imad
dc.contributor.authorPionteck, Thilo
dc.contributor.authorSaake, Gunter
dc.date.accessioned2022-01-27T13:26:43Z
dc.date.available2022-01-27T13:26:43Z
dc.date.issued2021
dc.description.abstractClassical database systems are now facing the challenge of processing high-volume data feeds at unprecedented rates as efficiently as possible while also minimizing power consumption. Since CPU-only machines hit their limits, co-processors like GPUs and FPGAs are investigated by database system designers for their distinct capabilities. As a result, database systems over heterogeneous processing architectures are on the rise. In order to better understand their potentials and limitations, in-depth performance analyses are vital. This paper provides interesting performance data by benchmarking a portable operator set for column-based systems on CPU, GPU, and FPGA – all available processing devices within the same system. We consider TPC‑H query Q6 and additionally a hash join to profile the execution across the systems. We show that system memory access and/or buffer management remains the main bottleneck for device integration, and that architecture-specific execution engines and operators offer significantly higher performance.de
dc.identifier.doi10.1007/s13222-021-00384-w
dc.identifier.pissn1610-1995
dc.identifier.urihttp://dx.doi.org/10.1007/s13222-021-00384-w
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/38027
dc.publisherSpringer
dc.relation.ispartofDatenbank-Spektrum: Vol. 21, No. 2
dc.relation.ispartofseriesDatenbank-Spektrum
dc.subjectCPU
dc.subjectFPGA
dc.subjectGPU
dc.subjectHeterogeneous database systems
dc.subjectOverlay architecture
dc.titleIn-Depth Analysis of OLAP Query Performance on Heterogeneous Hardwarede
dc.typeText/Journal Article
gi.citation.endPage143
gi.citation.startPage133

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