In this work, we propose a general-purpose coordinator-master-worker (GP-CMW) model to enable efficient and scalable simulation. The model supports distributed and parallel simulation over a heterogeneous computing node architecture with both multi-core CPUs and GPUs. The model aims at maximizing the hardware activity rate while reducing the overall management overhead. The proposed model includes five components: coordinator, priority abstraction layer, master, hardware abstraction layer, and worker. The proposed model is mainly optimized for large-scale simulation that relies on massive parallelizable events. Extensive set of experimental results shows that GP-CMW provides a significant gain from medium to intensive simulation load by exploiting heterogeneous computing resources including CPU and GPU. Regarding simulation runtime, the proposed GP-CMW model delivers a speedup that is 3.6 times faster than the CMW model.
General-purpose coordinator-master-worker model for efficient large-scale simulation over heterogeneous infrastructure
Journal of Simulation, August 2017, Volume 11, Issue 3, Springer
Systèmes de Communication
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in Journal of Simulation, August 2017, Volume 11, Issue 3, Springer and is available at : http://dx.doi.org/10.1057/s41273-016-0044-7
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