Energy and performance improvement using real-time DVFS for graph traversal on GPU

Abstract

Graphical-processing unit (GPU) handles massive data, effectively, as compared to CPU but has high power consumption which is a primary concern recently. A real-time dynamic voltage frequency scaling technique (DVFS) to save energy as well as improve performance, and to set the core and the memory frequency at a run time are proposed. Real-time DVFS is well investigated for saving energy and improving the performance by executing a breadth-first search (BFS) graph traversal algorithm from scalable heterogeneous computing (SHOC) benchmark suite. Two modes: energy saving and performance mode, can be realised by implementation of the proposed real-time DVFS algorithm. In energy saving mode, 28.2% energy can be saved with a performance improvement of 1.4%. On the other hand, 14.2% performance improvement is accomplished while maintaining the energy saving of 11.2% in performance mode. The proposed work is realised on K40c GPU received as a grant from NVidia.