Our Systems

SciNet is Canada’s largest supercomputing centre, and we run and make available a range of computing resources for Canadian researchers and innovators.   Below are a description of the systems, and links to find out more.

More technical information and the system status can be found on the SciNet documentation wiki.

Rouge AMD GPU Cluster

The Rouge cluster was donated to the University of Toronto by AMD as part of their COVID-19 HPC Fund support program. The cluster consists of 20 x86_64 nodes each with a single AMD EPYC 7642 48-Core CPU running at 2.3GHz with 512GB of RAM and 8 Radeon Instinct MI50 GPUs per node. The nodes are […]
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Mist GPU Cluster

The Mist system is a cluster of 54 IBM servers each with 4 NVIDIA V100 “Volta” GPUs with 32 GB memory each, and with NVLINKs in between. Each node of the cluster has 256GB RAM. It has InfiniBand EDR interconnection providing GPU-Direct RMDA capability. This system is a combination of the GPU extension to the […]
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A row of computer cabinets

Niagara Supercomputer

Niagara is a homogeneous cluster of initially 61,920 cores but expanded (in 2020) to 80,640 cores, owned by the University of Toronto and operated by SciNet. This system is intended to enable large parallel jobs of 1024 cores and more. It is the one of the most powerful supercomputers in Canada available for academic research. […]
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High Performance Storage System (HPSS)

The High Performance Storage System (HPSS) is a tape-backed hierarchical storage system that provides a significant portion of the allocated storage space at SciNet. It is a repository for archiving data that is not being actively used. Data can be returned to the active filesystem on the compute clusters when it is needed. SciNet’s HPSS […]
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Teach Cluster

Teach is a cluster of 672 cores at SciNet that has been assembled from older re-purposed compute hardware. Access to this small, homogeneous cluster is provided primarily for local teaching purposes. It is configured similarly to the production Niagara system. The cluster consists of 42 repurposed nodes each with 16 cores (two 8-core Intel Xeon […]
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