Automated performance prediction of message-passing parallel programs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Semi-empirical multiprocessor performance predictions
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
ScaLAPACK user's guide
Predicting parallel applications performance on non-dedicated cluster platforms
ICS '98 Proceedings of the 12th international conference on Supercomputing
Future Generation Computer Systems - Special issue on metacomputing
Predictive performance and scalability modeling of a large-scale application
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Prophesy: an infrastructure for performance analysis and modeling of parallel and grid applications
ACM SIGMETRICS Performance Evaluation Review
Prophesy: Automating the Modeling Process
AMS '01 Proceedings of the Third Annual International Workshop on Active Middleware Services
Proceedings of the 30th annual international symposium on Computer architecture
Performance Prediction in Production Environments
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Comparing Program Phase Detection Techniques
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Parallel program performance prediction using deterministic task graph analysis
ACM Transactions on Computer Systems (TOCS)
Pace--A Toolset for the Performance Prediction of Parallel and Distributed Systems
International Journal of High Performance Computing Applications
Modeling message-passing programs with a Performance Evaluating Virtual Parallel Machine
Performance Evaluation - Performance modelling and evaluation of high-performance parallel and distributed systems
Numerical Libraries and the Grid
International Journal of High Performance Computing Applications
A performance prediction framework for scientific applications
Future Generation Computer Systems
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
Methods of inference and learning for performance modeling of parallel applications
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Program phase detection and exploitation
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Centralized versus distributed schedulers for multiple bag-of-task applications
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Detecting phases in parallel applications on shared memory architectures
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A Process Scheduling Analysis Model Based on Grid Environment
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
Retelab: A geospatial grid web laboratory for the oceanographic research community
Future Generation Computer Systems
Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers
Journal of Parallel and Distributed Computing
Reliable performance prediction for multigrid software on distributed memory systems
Advances in Engineering Software
Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids
Journal of Grid Computing
Bacteria foraging optimization for protein sequence analysis on the grid
Future Generation Computer Systems
Flexible service selection with user-specific QoS support in service-oriented architecture
Journal of Network and Computer Applications
Coordinated rescheduling of Bag-of-Tasks for executions on multiple resource providers
Concurrency and Computation: Practice & Experience
Double auction-inspired meta-scheduling of parallel applications on global grids
Journal of Parallel and Distributed Computing
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Grids consist of both dedicated and non-dedicated clusters. For effective mapping of parallel applications on grid resources, a grid metascheduler has to evaluate different sets of resources in terms of predicted execution times for the applications when executed on the sets of resources. In this work, we have developed a comprehensive set of performance modeling strategies for predicting execution times of parallel applications on both dedicated and non-dedicated environments. Our strategies adapt to changing network and CPU loads on the grid resources. We have evaluated our strategies on 8, 16, 24 and 32-node clusters with random loads and load traces from a grid system. Our strategies give less than 30% average percentage prediction errors in all cases, which, to our knowledge, is the best reported for non-dedicated environments. We also found that grid scheduling using predictions of execution times from our performance modeling techniques will lead to perfect mapping of applications to resources in many cases.