Prophesy: an infrastructure for performance analysis and modeling of parallel and grid applications
ACM SIGMETRICS Performance Evaluation Review
Using Kernel Couplings to Predict Parallel Application Performance
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
A Portable Programming Interface for Performance Evaluation on Modern Processors
International Journal of High Performance Computing Applications
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Performance characteristics of the multi-zone NAS parallel benchmarks
Journal of Parallel and Distributed Computing - Special issue: 18th International parallel and distributed processing symposium
Online power-performance adaptation of multithreaded programs using hardware event-based prediction
Proceedings of the 20th annual international conference on Supercomputing
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
IEEE Transactions on Parallel and Distributed Systems
ACM SIGMETRICS Performance Evaluation Review - Special issue on the 1st international workshop on performance modeling, benchmarking and simulation of high performance computing systems (PMBS 10)
International Journal of High Performance Computing Applications
Evaluating Power-Monitoring Capabilities on IBM Blue Gene/P and Blue Gene/Q
CLUSTER '12 Proceedings of the 2012 IEEE International Conference on Cluster Computing
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MuMMI (Multiple Metrics Modeling Infrastructure) environment is an infrastructure that facilitates systematic measurement, modeling, and prediction of performance, power consumption and performance-power tradeoffs for parallel systems. MuMMI builds upon three existing frameworks: Prophesy for performance modeling and prediction of parallel applications, PAPI for hardware performance counter monitoring, and PowerPack for power measurement and profiling. In this paper, we present the MuMMI framework, which consists of an Instrumentor, Databases and Analyzer. The MuMMI Instrumentor provides automatic performance and power data collection and storage with low overhead. The MuMMI Databases extend the databases of Prophesy to store power and energy consumption and hardware performance counters' data with different CPU frequency settings. The MuMMI Analyzer extends the data analysis component of Prophesy to support power consumption and hardware performance counters, and it entails performance and power modeling, performance-power tradeoff and optimizations, and web-based automated modeling system. Currently, our MuMMI online automated performance and power modeling system uses four modeling techniques: curve fitting, parameterization, kernel coupling and performance-counters-based, we discuss the effort to automate the process of developing performance and power models for scientific applications online, and focus on exploring performance-counters-based performance and power modeling. The MuMMI environment is able to aid in performance and power data measurement, storage, modeling and prediction of scientific applications on XSEDE resources in XSEDE community.