Efficient Inter-Kernel Communication for OpenCL Database Operators on FPGAs

Drewes, Tobias; Joseph, Jan Moritz; Gurumurthy, Bala; Broneske, David; Saake, Gunter; Pionteck, Thilo

doi:10.1109/fpt.2018.00050

Cited by 2 publications

(1 citation statement)

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“…Another option is to implement multiple functions in the same FPGA design, which limits the amount of resources every functional unit can occupy, and therefore potentially reduces performance. We have already analyzed these shortcomings with respect to Intel OpenCL for FPGAs [15]. To combat this, modern FPGAs allow for smaller parts of the fabric to be reconfigured with different circuits during runtime, instead of just loading a complete design into the FPGA at power up.…”

Section: Fpgamentioning

confidence: 99%

In-Depth Analysis of OLAP Query Performance on Heterogeneous Hardware

et al. 2021

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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.

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Section: Fpgamentioning

confidence: 99%