In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware
dc.contributor.author | Broneske, David | |
dc.contributor.author | Drewes, Anna | |
dc.contributor.author | Gurumurthy, Bala | |
dc.contributor.author | Hajjar, Imad | |
dc.contributor.author | Pionteck, Thilo | |
dc.contributor.author | Saake, Gunter | |
dc.date.accessioned | 2022-01-27T13:26:43Z | |
dc.date.available | 2022-01-27T13:26:43Z | |
dc.date.issued | 2021 | |
dc.description.abstract | Classical 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.doi | 10.1007/s13222-021-00384-w | |
dc.identifier.pissn | 1610-1995 | |
dc.identifier.uri | http://dx.doi.org/10.1007/s13222-021-00384-w | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/38027 | |
dc.publisher | Springer | |
dc.relation.ispartof | Datenbank-Spektrum: Vol. 21, No. 2 | |
dc.relation.ispartofseries | Datenbank-Spektrum | |
dc.subject | CPU | |
dc.subject | FPGA | |
dc.subject | GPU | |
dc.subject | Heterogeneous database systems | |
dc.subject | Overlay architecture | |
dc.title | In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware | de |
dc.type | Text/Journal Article | |
gi.citation.endPage | 143 | |
gi.citation.startPage | 133 |