Optimizing performance under thermal and power constraints for HPC data centers
Osman Sarood · 2014
Energy, power and resilience are the major challenges that the HPC community faces in moving to larger supercomputers. Data centers worldwide consumed energy equivalent to 235 billion kWh in 2010. A significant portion of that energy and power consumption is devoted to cooling. This thesis proposes a scheme based on a combination of limiting processor temperatures using Dynamic Voltage and Frequency Scaling (DVFS) and frequency-aware load balancing that reduces cooling energy consumption and prevents hot spot formation. Recent reports have expressed concern that reliability at the exascale level could degrade to the point where failures become a norm rather than an exception. HPC researchers are focusing on improving existing fault tolerance protocols to address these concerns. Research on improving hardware reliability has also been making progress independently. A second component of this thesis tries to bridge this gap and explore the potential of combining both software and hardware aspects towards improving reliability of HPC machines. Finally, the 10MW consumption of present day HPC systems is certainly becoming a bottleneck. Although energy bills will significantly increase with machine size, power consumption is