Metrics for Evaluating Energy Saving Techniques for Resilient HPC Systems

Abstract

The metrics used for evaluating energy saving techniques for future HPC systems are critical to the correct assessment of proposed methods. Current predictions forecast that overcoming reduced system reliability, increased power requirements and energy consumption will be a major design challenge for future systems. Modern runtime energy-saving research efforts do not take into account the energy spent providing reliability. They also do not account for the increase in the probability of failure during application execution due to runtime overhead from energy saving methods. While this is very reasonable for current systems, it is insufficient for future generation systems. By taking into account the energy consumption ramifications of increased runtimes on system reliability, better energy saving techniques can be developed. This paper demonstrates how to determine the impact of runtime energy conservation methods within the context of failure-prone large scale systems. In addition, a survey of several energy savings methodologies is conducted and an analysis is performed with respect to their effectiveness in an environment in which failures occur.

Using architecture information and real-time resource state to reduce power consumption and communication costs in parallel applications.

“…We demonstrated this technique both for single-node applications and for parallel multi-node MPI+OpenMP applications. We demonstrated reductions in power consumption of 7.4% in the Lulesh parallel MPI+OpenMP application with no increase in application execution time [51,29].…”

“…Therefore by decreasing the number of these events, even more energy is saved. Figure 2.4 shows the potential benefits based on production checkpoint and restart parameters [29]. Furthermore, improvements in power controls of future microprocessors will make changing power states easier and more effective.…”

Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments

“…e study in [14] presents how to adapt performance measuring tools for energy efficiency management of parallel applications, specifically the libadapt library and an OpenMP wrapper. e study in [15] presents a survey of several energy savings methodologies with analysis concerning their effectiveness in an environment in which failures do occur. Energy costs of reliability are considered.…”