The major contributions of MuMI will include the following:

  • Extension of Prophesy’s performance modeling interface and database component to encompass multicore and to incorporate power parameters and metrics into the performance models.
  • Extension of PAPI’s widely used hardware performance monitoring library to include the collection and interpretation of relevant data for various components of multicore systems.
  • Extension of the PowerPack power-performance measurement, profiling, analysis and optimization framework to multicore architectures, enabling measurement of power consumption at component (e.g. processor core) and function-level granularities.
  • Development of modeling and analysis techniques that can be used to explore the performance and power optimization space of multicore systems, especially targeting resource contention issues.

On multicore systems, limitations related to sharing of resources can adversely affect the ability of applications to scale to use all available cores. Types of resource contention that can occur include shared cache contention, memory bus contention, and network interface contention. In the first few months of the project, we have designed a methodology to use hardware counters to detect and diagnose various types of resource contention. We have used this methodology in initial experiments to detect cache and memory bus contention when running the NAS Parallel Benchmarks (version 2.3 with OpenMP) on a 16-cire Intel Tigerton system.  Each socket has a quad-core chip and each chip has two dual-core shared L2 caches. We detected a significant amount of L2 cache contention with some of the benchmarks. The detailed results will be published in a technical report.

For online discussion about the MuMI project, see the MuMI wiki at http://wiki.mumi-tool.org/



Mar 30 2017 Admin Login