# Arbor -- a morphologically-detailed neural network simulation library for contemporary high-performance computing architectures

arXiv: https://arxiv.org/abs/1901.07454 · HTML: https://mlsanity.com/paper/1901.07454/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jan 2019.

## Built on by (most cited first, 1 of 1)

- [Tricking AI chips into Simulating the Human Brain: A Detailed Performance Analysis](https://mlsanity.com/paper/2301.13637/) (2023)

## Abstract (arXiv)

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. HPC, GPU, neuroscience, neuron, software