PDL ABSTRACT

Active Disk Meets Flash: A Case for Intelligent SSDs

Proceedings of the ACM Int'l Conference on Supercomputing (ICS), Eugene, OR, June 2013.

Sangyeun Cho1,2, Chanik Park3, Hyunok Oh4, Sungchan Kim5, Youngmin Yi6, Gregory R. Ganger7

1Memory Solutions Lab., Memory Division, Samsung Electronics Co., Korea
2Computer Science Department, University of Pittsburgh, USA
3Memory Division, Samsung Electronics Co., Korea
4Department of Information Systems, Hanyang University, Korea
5Division of Computer Science and Engineering, Chonbuk Nat'l University, Korea
6School of Electrical and Computer Engineering, University of Seoul, Korea
7Department of Electrical and Computer Engineering, Carnegie Mellon University, USA

http://www.pdl.cmu.edu/

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 (2-4× 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 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 2% increase in hardware cost over a traditional SSD, an iSSD can provide 2-4× performance increases and 5-27× energy efficiency gains for a range of data-intensive computations.

KEYWORDS: Data-intensive computing, energy-efficient computing, storage systems

FULL PAPER: pdf

 

 

 

© 2014. Last updated 28 May, 2013