Kiar Gregory, Brown Shawn T, Glatard Tristan, Evans Alan C
Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.
Front Neuroinform. 2019 Mar 5;13:12. doi: 10.3389/fninf.2019.00012. eCollection 2019.
Neuroscience has been carried into the domain of big data and high performance computing (HPC) on the backs of initiatives in data collection and an increasingly compute-intensive tools. While managing HPC experiments requires considerable technical acumen, platforms, and standards have been developed to ease this burden on scientists. While web-portals make resources widely accessible, data organizations such as the Brain Imaging Data Structure and tool description languages such as Boutiques provide researchers with a foothold to tackle these problems using their own datasets, pipelines, and environments. While these standards lower the barrier to adoption of HPC and cloud systems for neuroscience applications, they still require the consolidation of disparate domain-specific knowledge. We present Clowdr, a lightweight tool to launch experiments on HPC systems and clouds, record rich execution records, and enable the accessible sharing and re-launch of experimental summaries and results. Clowdr uniquely sits between web platforms and bare-metal applications for experiment management by preserving the flexibility of do-it-yourself solutions while providing a low barrier for developing, deploying and disseminating neuroscientific analysis.
在数据收集举措以及计算强度日益增大的工具的推动下，神经科学已进入大数据和高性能计算（HPC）领域。虽然管理HPC实验需要相当的技术才能，但已开发出平台和标准来减轻科学家的这一负担。网络门户使资源广泛可用，而诸如脑成像数据结构之类的数据组织以及诸如精品店（Boutiques）之类的工具描述语言为研究人员提供了利用自己的数据集、管道和环境来解决这些问题的立足点。虽然这些标准降低了神经科学应用采用HPC和云系统的障碍，但它们仍然需要整合不同领域的特定知识。我们展示了Clowdr，这是一种轻量级工具，用于在HPC系统和云上启动实验、记录丰富的执行记录，并实现实验总结和结果的可访问共享与重新启动。Clowdr独特地介于网络平台和裸机应用程序之间用于实验管理，它保留了自行解决方案的灵活性，同时为开发、部署和传播神经科学分析提供了较低的障碍。
