Performance estimation in a massively parallel system
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Predicting parallel applications performance on non-dedicated cluster platforms
ICS '98 Proceedings of the 12th international conference on Supercomputing
MPI-SIM: using parallel simulation to evaluate MPI programs
Proceedings of the 30th conference on Winter simulation
Performance prediction of large parallel applications using parallel simulations
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
On Performance Prediction of Parallel Computations with Precedent Constraints
IEEE Transactions on Parallel and Distributed Systems
Basic Linear Algebra Subprograms for Fortran Usage
ACM Transactions on Mathematical Software (TOMS)
Predictive performance and scalability modeling of a large-scale application
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
A Model for Moldable Supercomputer Jobs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
A framework for performance modeling and prediction
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Stealing cycles: Can we get along?
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
DPS - Dynamic Parallel Schedules
HIPS '03 Proceedings of the Eighth International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS'03)
A Malleable-Job System for Timeshared Parallel Machines
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Parallel program performance prediction using deterministic task graph analysis
ACM Transactions on Computer Systems (TOCS)
Implementing Malleability on MPI Jobs
Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques
Fault-Tolerant Parallel Applications with Dynamic Parallel Schedules
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 16 - Volume 17
Design and Implementation of the ScaLAPACK LU, QR, and Cholesky Factorization Routines
Scientific Programming
Towards an intelligent grid scheduling system
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
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Dynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. Detailed simulations can help identify allocation strategies and problem decomposition parameters that increase the efficiency of parallel applications. We describe a simulation framework supporting dynamic node allocation which, given a simple cluster model, predicts the running time of parallel applications taking CPU and network sharing into account. Simulations can be carried out without needing to modify the application code. Thanks to partial direct execution, simulation times and memory requirements are reduced. In partial direct execution simulations, the application's parallel behavior is retrieved via direct execution, and the duration of individual operations is obtained from a performance prediction model or from prior measurements. Simulations may then vary cluster model parameters, operation durations and problem decomposition parameters to analyze their impact on the application performance and identify the limiting factors. We implemented the proposed techniques by adding direct execution simulation capabilities to the Dynamic Parallel Schedules parallelization framework. We introduce the concept of dynamic efficiency to express the resource utilization efficiency as a function of time. We verify the accuracy of our simulator by comparing the effective running time, respectively the dynamic efficiency, of parallel program executions with the running time, respectively the dynamic efficiency, predicted by the simulator under different parallelization and dynamic node allocation strategies.