人脑模拟的MPI+OpenMP任务可扩展性:人脑计划

Pedro Valero-Lara, R. Sirvent, Antonio J. Peña, X. Martorell, Jesús Labarta
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引用次数: 7

摘要

人类大脑行为的模拟是当今最具雄心的挑战之一,具有无穷无尽的重要应用。我们可以在美国、欧洲和日本找到许多不同的倡议,试图实现这样一个具有挑战性的目标。在这项工作中,我们专注于最重要的欧洲计划(人脑计划)和其中一个工具(Arbor)。该工具通过计算神经元形态上的电压电容来模拟神经元网络中触发的尖峰,是当今最精确的模拟器之一。在目前的工作中,我们评估了在Arbor模拟器上使用MPI+OpenMP任务。在本文中,我们介绍了Arbor工具的主要特征,以及如何通过使用MPI+OpenMP任务有效地管理这些特征。我们证明,即使在使用最多32个节点计算相对较低的工作负载(神经元数量)时,这种方法也能够实现良好的扩展。我们的目标不仅包括实现基于MPI的高度可扩展的实现,而且还包括通过使用MPI+OpenMP任务开发一个具有高度抽象的工具,而不会失去控制和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MPI+OpenMP Tasking Scalability for the Simulation of the Human Brain: Human Brain Project
The simulation of the behavior of the Human Brain is one of the most ambitious challenges today with a non-end of important applications. We can find many different initiatives in the USA, Europe and Japan which attempt to achieve such a challenging target. In this work we focus on the most important European initiative (Human Brain Project) and on one of the tools (Arbor). This tool simulates the spikes triggered in a neuronal network by computing the voltage capacitance on the neurons' morphology, being one of the most precise simulators today. In the present work, we have evaluated the use of MPI+OpenMP tasking on top of the Arbor simulator. In this paper, we present the main characteristics of the Arbor tool and how these can be efficiently managed by using MPI+OpenMP tasking. We prove that this approach is able to achieve a good scaling even when computing a relatively low workload (number of neurons) per node using up to 32 nodes. Our target consists of achieving not only a highly scalable implementation based on MPI, but also to develop a tool with a high degree of abstraction without losing control and performance by using MPI+OpenMP tasking.
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