Talapas provides over 2 Petabytes of capacity on its Spectrum Scale parallel file system (GPFS) served from an Elastic Storage System (ESS) in addition to access to local SSD scratch disk space for I/O intensive workloads. Below is the latest snapshot of node specifications available running on Dell PowerEdge C and R servers. The Talapas cluster continues to grow and evolve. The RACS team consulted with the Confederated Tribes of the Grand Ronde to choose this name, following a Northwest convention of using American Indian languages when naming supercomputers. Talapas takes its name from the Chinook word for coyote, who was an educator and keeper of knowledge. Since its inception in 2018, Talapas has supported over 1,400 researchers across 35 departments and labs and has run over 90 million hours of computation. It is also currently used to support teaching and student learning in degree programs across campus, including Bioinformatics, Biology, Business, Chemistry, Computer Science, Genomics, Earth Science, and Physics. Talapas is suitable for high-performance computing in a wide range of disciplines, including but not limited to bioengineering, computer science, data science, economics, education, genomics, linguistics, neuro-engineering, physics, the physical sciences, and psychology. The Slurm workload manager handles cluster resource management and job scheduling. Researchers can access Talapas through a command line interface or an easy-to-use web-based interface.
Numerous programming languages, compilers, and mathematical and scientific libraries are available cluster wide, including over 225 discipline-specific application packages and a large array of Python packages including machine learning specific packages such as TensorFlow, Keras, and PyTorch. Talapas is a heterogeneous cluster that includes compute nodes with Intel and AMD processors, Nvidia GPUs, large memory nodes, and large local scratch nodes.Ĭonnectivity throughout the cluster is via 100Gb/sec EDR InfiniBand with Spectrum Scale (GPFS) file system mounted across all cluster nodes. The University of Oregon’s HPC cluster, Talapas, is comprised of approximately 9,500 cores, 90 TB memory, 120 GPUs, and over 2 PB storage.
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