This report covers events at SC17 that focused on energy efficiency and highlights ongoing collaborations across the community to develop advanced software technologies for system energy and power management.
One of the primary challenges for exascale is the total cost and variability associated with the power consumed by not only the HPC system, but also the additional infrastructure supporting it. The engineering efforts that are being invested in designing an exascale machine are hindered by the tight power constraint of 20-30 MW. The motivation for controlling this cost differs drastically from one site to another. For some sites, external factors such as shortage of electricity, natural disasters (e.g. tsunamis and earthquakes), and government-issued mandates limit the supply of power. For others, limitations in the design of the facility that houses the system can lead to power shortages. Some sites are driving research efforts in this field with the goal of mitigating the impact of computation on the environment. Another motivation is to reduce electricity bill costs in order to improve future purchasing power for compute resources. Even sites that are not facing an immediate shortage of power are driven by an active interest to stay “ahead of the curve,” to improve system reliability and resiliency. These are especially of concern given the fact that variability in power draw in future systems (i.e. the delta between complete idle state to peak Linpack power during a full-system run) can be as high as 40 MW. In addition, any fault in software or hardware may lead to premature termination of applications, leading to additional power costs with zero gains.
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