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A GPU accelerated storage system

Abdullah Gharaibeh, Samer A. Kiswany, Sathish Gopalakrishnan, Matei Ripeanu
The University of British Columbia, Vancouver, Canada
In HPDC ’10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (2010), pp. 167-178.

@conference{gharaibeh2010gpu,

   title={A GPU accelerated storage system},

   author={Gharaibeh, A. and Al-Kiswany, S. and Gopalakrishnan, S. and Ripeanu, M.},

   booktitle={Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing},

   pages={167–178},

   year={2010},

   organization={ACM}

}

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Massively multicore processors, like, for example, Graphics Processing Units (GPUs), provide, at a comparable price, a one order of magnitude higher peak performance than traditional CPUs. This drop in the cost of computation, as any order-of-magnitude drop in the cost per unit of performance for a class of system components, triggers the opportunity to redesign systems and to explore new ways to engineer them to recalibrate the cost-to-performance relation.
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