Using virtualization to quantify power conservation via near-threshold voltage reduction for inherently resilient applications

Power efficiency nowadays is a mainstream pressing issue in High Performance Computing (HPC), due to limited power supply capability of current and projected supercomputers. As a promising solution, leveraging inherent application resilience to relax power requirements of HPC runs can effectively save power with minor/acceptable loss of output quality. However, the challenges of this approach lie in: (a) how to reduce power usage of HPC runs online within allowable maximum extent such that quality metrics of applications can be satisfied, and (b) how to identify potential intrinsic nature of fault tolerance in general for an application. Existing efforts to date fail to address both challenges systematically and efficiently. In this work, based on virtualization and near-threshold voltage reduction techniques, we propose an empirical framework named V-Power to save the most power for inherently resilient applications. As an integrated empirical system, our approach effectively addresses the two above challenges using quantitative and fine-grained application inherent resilience analysis and frequency-independent near-threshold voltage reduction. Experimental results for a wide spectrum of scientific applications running on a 40-core power-aware server demonstrate that V-Power is capable of saving power up to 12.3%, resulting in a failure rate with acceptable program outputs.