Central and Distributed GPU based Parallel Disk Systems for Data Intensive Applications | Zendy

Mais Nijim | Zendy; Soumya Saha | Zendy; Y.W. Nijim | Zendy

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Central and Distributed GPU based Parallel Disk Systems for Data Intensive Applications

Author(s) -

Mais Nijim,

Soumya Saha,

Y.W. Nijim

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.07.034

Subject(s) - computer science , scalability , reliability (semiconductor) , parallel computing , workload , cuda , graphics , distributed computing , power (physics) , operating system , physics , quantum mechanics

Parallel disk systems are capable of fulfilling rapidly increasing demands on both large storage capacity and high I/O performance. However, it is challenging to significantly increase disk I/O bandwidth for data-intensive workloads due to (1) reliability and instant processing of data requests under dynamic workload conditions, and (2) the optimum tradeoff between system scalability and data reliability in data-intensive systems. To increase computing performance and reduce power consumption, Graphics Processing Units (GPUs) will be used. As the architectures and data processing algorithms for GPU-based parallel disk systems are still in their infancy, this research will develop novel hardware and software architectures that include parallel GPU, flash disks, and disk arrays for data-intensive applications

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