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

AbstractParallel 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