Applied multivariate statistical analysis
Applied multivariate statistical analysis
Continuous profiling: where have all the cycles gone?
ACM Transactions on Computer Systems (TOCS)
ProfileMe: hardware support for instruction-level profiling on out-of-order processors
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Managing performance analysis with dynamic statistical projection pursuit
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Very high resolution simulation of compressible turbulence on the IBM-SP system
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Proceedings of the 14th international conference on Supercomputing
Performance analysis using the MIPS R10000 performance counters
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
A scalable cross-platform infrastructure for application performance tuning using hardware counters
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
MPX: Software for Multiplexing Hardware Performance Counters in Multithreaded Programs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
An empirical performance evaluation of scalable scientific applications
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
A General Predictive Performance Model for Wavefront Algorithms on Clusters of SMPs
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
Vertical profiling: understanding the behavior of object-priented applications
OOPSLA '04 Proceedings of the 19th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Online performance analysis by statistical sampling of microprocessor performance counters
Proceedings of the 19th annual international conference on Supercomputing
OOPSLA '05 Proceedings of the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
PerfExplorer: A Performance Data Mining Framework For Large-Scale Parallel Computing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Using hardware performance monitors to understand the behavior of java applications
VM'04 Proceedings of the 3rd conference on Virtual Machine Research And Technology Symposium - Volume 3
Analysis of input-dependent program behavior using active profiling
Proceedings of the 2007 workshop on Experimental computer science
Analysis of input-dependent program behavior using active profiling
ecs'07 Experimental computer science on Experimental computer science
Knowledge support and automation for performance analysis with PerfExplorer 2.0
Scientific Programming - Large-Scale Programming Tools and Environments
Space-efficient time-series call-path profiling of parallel applications
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Finding representative workloads for computer system design
Finding representative workloads for computer system design
Software—Practice & Experience
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Application classification through monitoring and learning of resource consumption patterns
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Automatic performance debugging of SPMD-style parallel programs
Journal of Parallel and Distributed Computing
Soft computing approach to performance analysis of parallel and distributed programs
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Statistical methods for automatic performance bottleneck detection in MPI based programs
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
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Contemporary microprocessors provide a rich set of integrated performance counters that allow application developers and system architects alike the opportunity to gather important information about workload behaviors. Current techniques for analyzing data produced from these counters use raw counts, ratios, and visualization techniques help users make decisions about their application performance. While these techniques are appropriate for analyzing data from one process, they do not scale easily to new levels demanded by contemporary computing systems. Very simply, this paper addresses these concerns by evaluating several multivariate statistical techniques on these datasets. We find that several techniques, such as statistical clustering, can automatically extract important features from the data. These derived results can, in turn, be fed directly back to an application developer, or used as input to a more comprehensive performance analysis environment, such as a visualization or an expert system.