Event graph visualization for debugging large applications
SPDT '96 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
Dynamic statistical profiling of communication activity in distributed applications
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A Dynamic Periodicity Detector: Application to Speedup Computation
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
An Algebra for Cross-Experiment Performance Analysis
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
OOPSLA '05 Proceedings of the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Performance feature identification by comparative trace analysis
Future Generation Computer Systems
Stardust: tracking activity in a distributed storage system
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Wavelet-based phase classification
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
MPI performance analysis tools on Blue Gene/L
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
A test suite for parallel performance analysis tools: Research Articles
Concurrency and Computation: Practice & Experience - European–American Working Group on Automatic Performance Analysis (APART)
Automatic analysis of inefficiency patterns in parallel applications: Research Articles
Concurrency and Computation: Practice & Experience - European–American Working Group on Automatic Performance Analysis (APART)
Preserving time in large-scale communication traces
Proceedings of the 22nd annual international conference on Supercomputing
Scalable load-balance measurement for SPMD codes
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Scaling molecular dynamics to 3000 processors with projections: a performance analysis case study
ICCS'03 Proceedings of the 2003 international conference on Computational science
A performance prediction framework for scientific applications
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
A new data compression technique for event based program traces
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Towards scalable event tracing for high end systems
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
Scalable event trace visualization
Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing
A similarity measure for time, frequency, and dependencies in large-scale workloads
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Trace-based performance analysis for the petascale simulation code FLASH
International Journal of High Performance Computing Applications
Trace profiling: Scalable event tracing on high-end parallel systems
Parallel Computing
Big wireless measurement campaigns: are they really worth the price?
Proceedings of the 4th ACM international workshop on Hot topics in planet-scale measurement
Concurrency and Computation: Practice & Experience
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Event traces are required to correctly diagnose a number of performance problems that arise on today's highly parallel systems. Unfortunately, the collection of event traces can produce a large volume of data that is difficult, or even impossible, to store and analyze. One approach for compressing a trace is to identify repeating trace patterns and retain only one representative of each pattern. However, determining the similarity of sections of traces, i.e., identifying patterns, is not straightforward. In this paper, we investigate pattern-based methods for reducing traces that will be used for performance analysis. We evaluate the different methods against several criteria, including size reduction, introduced error, and retention of performance trends, using both benchmarks with carefully chosen performance behaviors, and a real application.