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On GPU’s viability as a middleware accelerator

Samer A. Kiswany, Abdullah Gharaibeh, Elizeu S. Neto, Matei Ripeanu
Electrical and Computer Engineering Department, The University of British Columbia, Vancouver, BC Canada, V6T 1Z4
Cluster Computing, Vol. 12, No. 2. (2009), pp. 123-140.

@article{al2009gpu,

   title={On GPUs viability as a middleware accelerator},

   author={Al-Kiswany, S. and Gharaibeh, A. and Santos-Neto, E. and Ripeanu, M.},

   journal={Cluster Computing},

   volume={12},

   number={2},

   pages={123–140},

   year={2009},

   publisher={Springer}

}

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Today Graphics Processing Units (GPUs) are a largely underexploited resource on existing desktops and a possible cost-effective enhancement to high-performance systems. To date, most applications that exploit GPUs are specialized scientific applications. Little attention has been paid to harnessing these highly-parallel devices to support more generic functionality at the operating system or middleware level. This study starts from the hypothesis that generic middleware-level techniques that improve distributed system reliability or performance (such as content addressing, erasure coding, or data similarity detection) can be significantly accelerated using GPU support.
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