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Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures

机译:Arbor —形态详细的神经网络仿真库,用于当代高性能计算体系结构

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We introduce Arbor, a performance portable library for simulation of large networks of multi-compartment neurons on HPC systems. Arbor is open source software, developed under the auspices of the HBP. The performance portability is by virtue of back-end specific optimizations for x86 multicore, Intel KNL, and NVIDIA GPUs. When coupled with low memory overheads, these optimizations make Arbor an order of magnitude faster than the most widely-used comparable simulation software. The single-node performance can be scaled out to run very large models at extreme scale with efficient weak scaling.
机译:我们引入Arbor,一种性能可移植的库,用于在HPC系统上模拟大型多隔室神经元网络。 Arbor是在HBP的主持下开发的开源软件。性能的可移植性是通过针对x86多核,英特尔KNL和NVIDIA GPU的后端特定优化而实现的。加上较低的内存开销,这些优化使Arbor比最广泛使用的同类仿真软件快一个数量级。可以扩展单节点性能,以有效的弱缩放在极端规模下运行非常大的模型。

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