Experimental Estimation and Analysis of the Power Efficiency of CUDA Processing Element on SIMD Computing

Estimating and analyzing the power consuming features of a program on a hardware platform is important in High Performance Computing (HPC) program optimization. A reasonable evaluation can help to handle the critical design constraints at the level of software, choosing preferable algorithm in order to reach the best power performance. In this paper we illustrate a simple experimental method to examine SIMD computing on GPU and Multicore computers. By measuring the power of each component and analyzing the execution speed, power parameters are captured, the power consuming features are analyzed and concluded. Thereafter power efficiency of any scale of this SIMD computation on the platform can be simply evaluated based on the features. The precision of above approximation is examined and detailed error analysis has been provided. The power consumption prediction has been validated by comparative analysis on real systems.