Disk I/O Performance-per-Watt Analysis for Cloud Computing

Assessing disk I/O performance and power consumption associated with a given cloud workload is important especially for workloads that are bounded by disk I/O. Disk performance becomes a bottleneck for achieving higher performance and lower power consumption especially when memory size is not enough to process large blocks of data. This will lead to a negative impact on the Quality-of-Service (QoS). In this paper, we analyze disk I/O performance by assessing the disk bandwidth and latency for different reads and writes configurations for sequential and random patterns. The systems used are based on ATOM D525 and Xeon X5660 processors. We analyze power consumption for both systems and provide a performance-per-watt optimum operation point. We also propose an estimation method which estimates disk latency at different disk queue depth settings. The estimation method is verified to estimate disk latency with < 5% error margin.