Impact of processor frequency scaling on performance and energy consumption for WZ factorization on multicore architecture

Abstract

With the growing demand for computing power, new multicore architectures have emerged to provide better performance. Reducing their energy consumption is one of the main challenges in achieving high performance computing. Current research trends develop new software and hardware techniques to achieve the best performance and energy compromise. In this work, we investigate the effect of processor frequency scaling using Dynamic Voltage Frequency Scaling on performance and energy consumption for the WZ factorization. This factorization is implemented both without optimization techniques and with strip mining. This technique involves transforming the program loop to improve program performance. Based on time and energy tests, we have shown that for the WZ factorization algorithm, regardless of the presence of manual optimization, it pays to reduce the frequency to save energy without losing performance. The conclusion can be extended to analogous algorithmsalso having a high ratio of memory access to computational operations.