Task spreading and shrinking on a network of workstations with various edge classes

Jacob, Joseph; Lee, S.-Y.

doi:10.1109/icpp.1996.538573

Cited by 2 publications

(2 citation statements)

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“…where the R i represent the adjusted numbers of tasks per processor (8). The algebraic mean M( R) and the algebraic variance V( R) are defined in (7).…”

Section: Lemma 3 the Expected Value Of The Algebraic Variance Of Thementioning

confidence: 99%

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A Framework to Analyze the Performance of Load Balancing Schemes for Ensembles of Stochastic Simulations

Ahn

Sandu

Watson

et al. 2014

Int J Parallel Prog

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Abstract-Ensembles of simulations are employed to estimate the statistics of possible future states of a system, and are widely used in important applications such as climate change and biological modeling. Ensembles of runs can naturally be executed in parallel. However, when the CPU times of individual simulations vary considerably, a simple strategy of assigning an equal number of tasks per processor can lead to serious work imbalances and low parallel efficiency. This paper presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms for ensembles of simulations where many tasks are mapped onto each processor, and where the individual compute times vary considerably among tasks. Four load balancing strategies are discussed: most-dividing, all-redistribution, random-polling, and neighbor-redistribution. Simulation results with a stochastic budding yeast cell cycle model is consistent with the theoretical analysis. It is especially significant that there is a provable global decrease in load imbalance for the local rebalancing algorithms due to scalability concerns for the global rebalancing algorithms. The overall simulation time is reduced by up to 25%, and the total processor idle time by 85%.Index Terms-Dynamic load balancing (DLB), probabilistic framework analysis, ensemble simulations, stochastic simulation algorithm (SSA), high-performance computing (HPC), budding yeast cell cycle.

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“…where the R i represent the adjusted numbers of tasks per processor (8). The algebraic mean M( R) and the algebraic variance V( R) are defined in (7).…”

Section: Lemma 3 the Expected Value Of The Algebraic Variance Of Thementioning

confidence: 99%

“…A large body of research literature is available on static and dynamic load balancing (DLB) techniques [4], [5], [6], [7], [8]. Two classes of DLB methods are widely used: scheduling (work-sharing) schemes [9], [10], [11] and work-stealing schemes [12], [13], [14].…”

mentioning

confidence: 99%