SmartSSD: FPGA Accelerated Near-Storage Data Analytics on SSD
Faced with the increasing disparity between SSD throughput and CPU-based compute capabilities, there have been growing interests to move compute closer to storage and accelerate the data analytic workloads. In this letter, we propose SmartSSD, an SSD with onboard FPGA, which enables offloading compu...
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| Veröffentlicht in: | IEEE computer architecture letters 2020-07, Vol.19 (2), p.110-113 |
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| container_title | IEEE computer architecture letters |
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| creator | Lee, Joo Hwan Zhang, Hui Lagrange, Veronica Krishnamoorthy, Praveen Zhao, Xiaodong Ki, Yang Seok |
| description | Faced with the increasing disparity between SSD throughput and CPU-based compute capabilities, there have been growing interests to move compute closer to storage and accelerate the data analytic workloads. In this letter, we propose SmartSSD, an SSD with onboard FPGA, which enables offloading computation within SSD. We perform a detailed model-based evaluation to evaluate the end-to-end performance and energy benefit of SmartSSD for the representative data analytic workloads with Spark SQL and Parquet columnar data format. Our evaluation shows that SmartSSD has the potential to have a transformative impact when building a high performance data analytic system, which enables 3.04x performance improvement and consuming only 45.8 percent of energy compared to the conventional CPU-based approach. |
| doi_str_mv | 10.1109/LCA.2020.3009347 |
| format | Article |
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| subjects | Bandwidth Computation offloading Data analysis data analytics Field programmable gate arrays IP networks Mathematical analysis parquet Performance evaluation Pipelines Query languages Random access memory SmartSSD spark SSD Throughput Workload Workloads |
| title | SmartSSD: FPGA Accelerated Near-Storage Data Analytics on SSD |
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