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Evaluation of Two Parallel Finite Element Implementations of the Time-Dependent Advection Diffusion Problem: GPU versus Cluster Considering Time and Energy Consumption

机译:评估时间依赖性的平行扩散问题的两个平行有限元实现:GPU与集群考虑时间和能量消耗

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We analyze two parallel finite element implementations of the 2D time-dependent advection diffusion problem, one for multi-core clusters and one for CUDA-enabled GPUs, and compare their performances in terms of time and energy consumption. The parallel CUDA-enabled GPU implementation was derived from the multi-core cluster version. Our experimental results show that a desktop machine with a single CUDA-enabled GPU can achieve performance higher than a 24-machine (96 cores) cluster in this class of finite element problems. Also, the CUDA-enabled GPU implementation consumes less than one twentieth of the energy (Joules) consumed by the multi-core cluster implementation while solving a whole instance of the finite element problem.
机译:我们分析了2D时间依赖性的前进扩散问题的两个并行有限元实现,一个用于多核集群,一个用于支持CUDA的GPU,并在时间和能量消耗方面进行比较它们的性能。启用了并行的CUDA的GPU实现是从多核群集版本派生的。我们的实验结果表明,具有单一CUDA的GPU的台式机可以在这类有限元问题中实现高于24机(96个核心)集群的性能。此外,CUDA的GPU实现消耗了多核群集实现消耗的低于一度的能量(焦耳),同时解决了有限元问题的整个实例。

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