PDL Abstract

Active Disk Meets Flash: A Case for Intelligent SSDs

Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-11-115. Dec. 2011.

Sangyeun Cho (University of Pittsburgh), Chanik Park (Samsung Electronics Co., Ltd.),
Hyunok Oh (Hanyang Univesity), Sungchan Kim (Chonbuk National University),
Youngmin Yi (University of Seoul) and Gregory R. Ganger (Carnegie Mellon University)

Carnegie Mellon University
Pittsburgh, PA 15213

Intelligent solid-state drives (iSSDs) allow execution of limited application functions (e.g., data filtering or aggregation) on their internal hardware resources, exploiting SSD characteristics and trends to provide large and growing performance and energy efficiency benefits. Most notably, internal flash media bandwidth can be significantly (2–4X or more) higher than the external bandwidth with which the SSD is connected to a host system, and the higher internal bandwidth can be exploited within an iSSD. Also, SSD bandwidth is quite high and projected to increase rapidly over time, creating a substantial energy cost for streaming of data to an external CPU for processing, which can be avoided via iSSD processing. This paper makes a case for iSSDs by detailing these trends, quantifying the potential benefits across a range of application activities, describing how SSD architectures could be extended cost-effectively, and demonstrating the concept with measurements of a prototype iSSD running simple data scan functions. Our analyses indicate that, with less than a 4% increase in hardware cost over a traditional SSD, an iSSD can provide 2–4X performance increases and 5–27X energy efficiency gains for a range of data-intensive computations.

KEYWORDS: Active Storage, Data-Intensive Computing, Energy-Efficient Data Processing, Reconfigurable Processor.

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