Exploring the Energy-Time Tradeoff in MPI Programs on a Power-Scalable Cluster
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Online power-performance adaptation of multithreaded programs using hardware event-based prediction
Proceedings of the 20th annual international conference on Supercomputing
Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes
IEEE Transactions on Parallel and Distributed Systems
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High Performance Computing (HPC) is a key technology for modern researchers enabling scientific advances through simulation where experiments are either technically impossible or financially not feasible to conduct and theory is not applicable. However, the high degree of computational power available from today's supercomputers comes at the cost of large quantities of electrical energy being consumed. This paper aims to give an overview of the current state of the art and future techniques to reduce the overall power consumption of HPC systems and sites. We believe that a holistic approach for monitoring and operation at all levels of a supercomputing site is necessary. Thus, we do not only concentrate on the possibility of improving the energy efficiency of the compute hardware itself, but also of site infrastructure components for power distribution and cooling. Since most of the energy consumed by supercomputers is converted into heat, we also outline possible technologies to re-use waste heat in order to increase the Power Usage Effectiveness (PUE) of the entire supercomputing site.