利用谷歌云平台模拟大脑神经元回路的大规模模型。

Subhashini Sivagnanam, Wyatt Gorman, Donald Doherty, Samuel A Neymotin, Stephan Fang, Hermine Hovhannisyan, William W Lytton, Salvador Dura-Bernal
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引用次数: 6

摘要

生物物理详细建模提供了一种无与伦比的方法来整合来自许多不同实验研究的数据,并以高精度操作和探索结果脑回路模拟。我们开发了一个大脑运动皮层回路的详细模型,模拟了超过10,000个生物物理上详细的神经元和3000万个突触连接。通过使用网格搜索、参数扫描和进化算法进行参数探索,实现了皮质模型参数和响应的优化和评估。这需要运行数以万计的模拟,需要大量的计算资源。本文介绍了我们建立和使用Google Compute Platform (GCP)和Slurm来运行这些大规模模拟的经验。我们描述了在此过程中出现的问题的最佳实践和解决方案,并介绍了在GCP上运行模拟的初步结果。
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Simulating Large-scale Models of Brain Neuronal Circuits using Google Cloud Platform.

Biophysically detailed modeling provides an unmatched method to integrate data from many disparate experimental studies, and manipulate and explore with high precision the resultin brain circuit simulation. We developed a detailed model of the brain motor cortex circuits, simulating over 10,000 biophysically detailed neurons and 30 million synaptic connections. Optimization and evaluation of the cortical model parameters and responses was achieved via parameter exploration using grid search parameter sweeps and evolutionary algorithms. This involves running tens of thousands of simulations requiring significant computational resources. This paper describes our experience in setting up and using Google Compute Platform (GCP) with Slurm to run these large-scale simulations. We describe the best practices and solutions to the issues that arose during the process, and present preliminary results from running simulations on GCP.

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PEGR: a management platform for ChIP-based next generation sequencing pipelines. Simulating Large-scale Models of Brain Neuronal Circuits using Google Cloud Platform.
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