Computer Science - Research and Development

, Volume 27, Issue 4, pp 235–243 | Cite as

Flexible workload generation for HPC cluster efficiency benchmarking

  • Daniel Molka
  • Daniel Hackenberg
  • Robert Schöne
  • Timo Minartz
  • Wolfgang E. Nagel
Special Issue Paper

Abstract

The High Performance Computing (HPC) community is well-accustomed to the general idea of benchmarking. In particular, the TOP500 ranking as well as its foundation—the Linpack benchmark—have shaped the field since the early 1990s. Other benchmarks with a larger workload variety such as SPEC MPI2007 are also well-accepted and often used to compare and rate a system’s computational capability. However, in a petascale and soon-to-be exascale computing environment, the power consumption of HPC systems and consequently their energy efficiency have been and continue to be of growing importance, often outrivaling all aspects that focus narrowly on raw compute performance. The Green500 list is the first major attempt to rank the energy efficiency of HPC systems. However, its main weakness is again the focus on a single, highly compute bound algorithm. Moreover, its method of extrapolating a system’s power consumption from a single node is inherently error-prone. So far, no benchmark is available that has been developed from ground up with the explicit focus on measuring the energy efficiency of HPC clusters. We therefore introduce such a benchmark that includes transparent energy measurements with professional power analyzers. Our efforts are based on well-established standards (C, POSIX-IO and MPI) to ensure a broad applicability. Our well-defined and comprehensible workloads can be used to, e.g. compare the efficiency of HPC systems or to track the effects of power saving mechanisms that can hardly be understood by running regular applications due to their overwhelming complexity.

Keywords

Power consumption Energy efficiency Benchmark High performance computing Workload generation 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Daniel Molka
    • 1
  • Daniel Hackenberg
    • 1
  • Robert Schöne
    • 1
  • Timo Minartz
    • 2
  • Wolfgang E. Nagel
    • 1
  1. 1.Center for Information Services and HPC (ZIH)Technische Universität DresdenDresdenGermany
  2. 2.Department of InformaticsUniversity of HamburgHamburgGermany

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