A GPU accelerated storage system

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. In this context, we focus on data storage: We explore the feasibility of harnessing the GPUs’ computational power to improve the performance, reliability, or security of distributed storage systems. In this context we present the design of a storage system prototype that uses GPU offloading to accelerate a number of computationally intensive primitives based on hashing. We evaluate the performance of this prototype under two configurations: as a content addressable storage system that facilitates online similarity detection betw...

• Type: Conference
• Year: 2010
• Where: HPDC
• Authors: Abdullah Gharaibeh, Samer Al-Kiswany, Sathish Gopalakrishnan, Matei Ripeanu
• Keywords: Distributed And Parallel Computing, HPDC 2010, Performance, Processors, Systems