Energy Efficient Job Scheduling with DVFS for CPU-GPU Heterogeneous Systems
Vincent Chau, Xiaowen Chu, Hai Liu, Yiu-Wing Leung · 2017
The past few years have witnessed significant growth in the computational capabilities of GPUs. The race for computing performance makes the uses of many-core accelerators more necessary. However, GPUs consume a significant amount of energy as compared with CPUs. One way to reduce the energy consumption is to scale the speed and/or voltage of the processor. Typically, the faster the processor runs, the faster we finish jobs, but the more power is required by the processor. It is hence important to balance between performance and power consumption.