Datenbank Spektrum 21(2) - Juli 2021

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Zeitschriftenartikel
In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware
(Datenbank-Spektrum: Vol. 21, No. 2, 2021) Broneske, David; Drewes, Anna; Gurumurthy, Bala; Hajjar, Imad; Pionteck, Thilo; Saake, Gunter
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.