Exploring the Energy-Time Tradeoff in MPI Programs on a Power-Scalable Cluster

Recently, energy has become an important issue in highperformance computing. For example, supercomputers that have energy in mind, such as BlueGene/L, have been built; the idea is to improve the energy efficiency of nodes. Our approach, which uses off-the-shelf, high-performance cluster nodes that are frequency scalable, allows energy saving by scaling down the CPU. This paper investigates the energy consumption and execution time of applications from a standard benchmark suite (NAS) on a power-scalable cluster. We study via direct measurement and simulation both intra-node and inter-node effects of memory and communication bottlenecks, respectively. Additionally, we compare energy consumption and execution time across different numbers of nodes. Our results show that a power-scalable cluster has the potential to save energy by scaling the processor down to lower energy levels. Furthermore, we found that for some programs, it is possible to both consume less energy and execute in les...

• Type: Conference
• Year: 2005
• Where: IPPS
• Authors: Vincent W. Freeh, Feng Pan, Nandini Kappiah, David K. Lowenthal, Robert Springer
• Keywords: Distributed And Parallel Computing, Energy Consumption, Execution Time, IPPS 2005, Power-scalable Cluster