Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
A Framework-Based Approach to the Development of Network-Aware Applications
IEEE Transactions on Software Engineering
Automatic node selection for high performance applications on networks
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Data mining: concepts and techniques
Data mining: concepts and techniques
Application-level scheduling on distributed heterogeneous networks
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Implementing a performance forecasting system for metacomputing: the Network Weather Service
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Basic Block Distribution Analysis to Find Periodic Behavior and Simulation Points in Applications
Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques
A framework for performance modeling and prediction
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Compact application signatures for parallel and distributed scientific codes
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Master/Slave Computing on the Grid
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Metascheduling: A Scheduling Model for Metacomputing Systems
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
A Resource Query Interface for Network-Aware Applications
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
An Evaluation of Linear Models for Host Load Prediction
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Characterizing and Predicting Program Behavior and its Variability
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Replicating memory behavior for performance prediction
LCR '04 Proceedings of the 7th workshop on Workshop on languages, compilers, and run-time support for scalable systems
Modeling application performance by convolving machine signatures with application profiles
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
SPAND: shared passive network performance discovery
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
Construction and evaluation of coordinated performance skeletons
HiPC'08 Proceedings of the 15th international conference on High performance computing
Scalable Communication Trace Compression
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Exploiting performance characterization of BLAST in the grid
Cluster Computing
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The performance skeleton of an application is a short running program whose execution time in any scenario reflects the estimated execution time of the application it represents. Such a skeleton can be employed to quickly estimate the performance of a large application under existing network and node sharing. This paper presents a framework for automatic construction of performance skeletons of a specified execution time and evaluates their use in performance prediction with CPU and network sharing. The approach is based on capturing the execution behavior of an application and automatically generating a synthetic skeleton program that reflects that execution behavior. The paper demonstrates that performance skeletons running for a few seconds can predict the application execution time fairly accurately. Relationship of skeleton execution time, application characteristics, and nature of resource sharing, to accuracy of skeleton based performance prediction, is analyzed in detail. The goal of this research is accurate performance estimation in heterogeneous and shared computation environments.