Heterogeneous Voltage Frequency Scaling of Data-Parallel Applications for Energy Saving on Homogeneous Multicore Platforms

In this paper, for the first time, we explore and establish the combined benefits of heterogeneous DVFS (dynamic voltage frequency scaling) control in improving the energy-performance behavior of data-parallel applications on shared-memory multicore systems. We propose to customize the clock frequency individually for the appropriately selected groups of cores corresponding to the diversified time of actual computation. In consequence, the advantage of up to 20% points over the homogeneous frequency scaling is achieved on the ccNUMA server with two 18-core Intel Xeon Gold 6240 containing 72 logical cores in total. The cost and efficiency of the proposed pruning algorithm for selecting heterogeneous DVFS configurations against the brute-force search are verified and compared experimentally.