Application configuration selection for energy-efficient execution on multicore systems

Modern computer systems are designed to balance performance and energy consumption. Several run-time factors, such as concurrency levels, thread mapping strategies, and dynamic voltage and frequency scaling (DVFS) should be considered in order to achieve optimal energy efficiency for a workload. Selecting appropriate run-time factors, however, is one of the most challenging tasks because the run-time factors are architecture-specific and workload-specific.While most existing works concentrate on either static analysis of the workload or run-time prediction results, in this paper, we present a hybrid two-step method that utilizes concurrency levels and DVFS settings to achieve the energy efficiency configuration for a workload. The experimental results based on a Xeon E5620 server with NPB and PARSEC benchmark suites show that the model is able to predict the energy efficient configuration accurately. On average, an additional 10 % EDP (Energy Delay Product) saving is obtained by using run-time DVFS for the entire system. An off-line optimal solution is used to compare with the proposed scheme. The experimental results show that the average extra EDP saved by the optimal solution is within 5 % on selective parallel benchmarks. We present a hybrid method to achieve an energy efficiency configuration.Our method utilizes concurrency levels, thread allocation, and DVFS settings.We propose a model to capture the relationship between C , P , and T in detail.We apply an analytical speedup model to predict an optimal/nearoptimal configuration.