UBC ML Computational Cluster

UBC ML 计算集群

• 批准号: RTI-2021-00485
• 负责人: Wood, Frank
• 金额: $ 10.93万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718685
• 关键词: UBC; ML; Computational; Cluster

Machine learning research relies heavily on the availability of computational resources. Unfortunately, due to high demand, not all faculty members are able to gain access to allocations on existing high performance computing facilities. Moreover, allocations on these systems, while suitable for extensive computation, are not designed for developmental work needed to reach a final model structure. Finally, the hardware available at these facilities is not necessarily most suited to machine learning applications, as the facilities are designed to service all disciplines. To resolve these issues, we propose setting up an extendable local computational cluster, equipped with the latest NVIDIA RTX-3090 and 100 TB of storage to support research performed by 5 faculty members and more than 50 graduate students and postdoctoral fellows in computer science and statistics, whose research is funded by NSERC, CIFAR, MITACS and other sources. This system is designed to complement allocations from existing high performance computing facilities such as Compute Canada and UBC ARC Sockeye. The system is designed to be extendable, so new hardware can be added if needed, and new faculty members can be given access in future years.

机器学习研究在很大程度上依赖于计算资源的可用性。不幸的是，由于高需求，并不是所有的教职员工都能够获得对现有高性能计算设施的分配。此外，这些系统的分配虽然适合广泛的计算，但不是为达到最终模型结构所需的发展工作而设计的。最后，这些设施的硬件并不一定最适合机器学习应用，因为这些设施是为所有学科设计的。