EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems

Abstract

Redundant array of inexpensive disks (RAID) based storage systems performance is limited to the sequential nature of the central processing unit (CPU), and they consume high amounts of energy because they need erasure coding for striping data and parity into storage devices. This paper proposed an energy-aware GPU based scheduling. The proposed scheduler differs from existing RAID in that it can reduce the number of CPU cycles and coding time. The proposed system generates parity by using a GPU, stripes parity at the initiator server and stripes data at the target server. We also apply an energy-aware scheduling scheme based on solid state disk-based data storage and hard disk drive-based parity storage. Experimental results show that the energy consumption by GPU-RAID is 45% less than Linux-RAID.