Through ACENET and the Digital Research Alliance of Canada (the Alliance) Federation, Atlantic Canadian researchers, post-secondary students and industry have access to supercomputing resources.

Used for complex numerical modelling, parallel computing, big data processing and analysis, machine learning/deep learning/artificial intelligence, and building platforms or portals in the cloud, the systems incorporate:

  • State-of-the-art High Performance Computing (HPC) and storage systems
  • Big data and data analytics tools and environments
  • A cloud computing and development environment
  • Leading edge Graphics Processing Unit (GPU) computing systems
  • High speed, secure file transfer through Compute Canada’s Globus Portal
  • Compute Canada’s extensive software library
  • The Genetics and Genomics Analysis Platform (GenAP)
  • Stable and secure data storage and back-up options accessed via your desktop

National Systems

These national systems have a combined 325,400 CPUs, 3286 GPUs, 51,557 virtual CPUs (cloud-based) and 416 virtual GPUs. The total storage capacity is 150 PBs on disks for fast data access, and over 400 PBs of tape storage. Featuring cutting-edge technology, they are available free of charge to research teams from post-secondary institutions. 

Cloud Resources

Located at the University of Victoria, Arbutus is an OpenStack cloud, hosting virtual machines and other cloud workloads. The system, provided by Lenovo, has 14,968 CPU cores across 456 nodes, 146,944 GBs of RAM and accesses 5.7 PBs of persistent Ceph storage. Note that other cloud resources are available for a combined total of 17,272 cores nationally.

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Located at the École de technologie supérieure in Montreal, Béluga is a general purpose cluster with 34,880 cores. Béluga, composed of a variety of nodes – including large memory nodes and GPU nodes with Turbo Boost activated – is designed to accommodate a broad range of workloads. 

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Located at Simon Fraser University, the Cedar system is a heterogeneous cluster (CPUs and GPUs), with 94,528 CPU cores, suitable for a variety of workloads. 

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Located at the University of Waterloo, Graham is a heterogeneous cluster, suitable for a variety of workloads. It has a small OpenStack partition, and includes local storage on nodes. Specifications include 41,548 CPU cores across a diverse set of node types, including GPU nodes. The Graham system is entirely liquid cooled, using rear-door heat exchangers.  

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With 80,000 CPU cores, 422 TB of memory and 25 PB of disk storage, Narval is comparable in power to 10,000 state-of-the-art laptops with 25,000 times the storage and memory. Specifically designed to meet the computational needs of the scientific community, it features more than 632 state-of-the-art graphics processing units (GPUs) that are particularly well-suited to work in artificial intelligence.

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Located at the University of Toronto, Niagara has 80,640 CPU cores. This system has 202 GBs (188 GiB) of RAM per node and offers 7 PBs of scratch and 2 PBs of project storage space. Mellanox EDR InfiniBand is used to create a Dragonfly+ network topology featuring adaptive routing to provide the high-speed low-latency communications necessary for large-scale full-system simulations. A 256 Terabyte (TB) burst-buffer in this cluster helps improve performance for data-intensive work loads.   

Technical help   Technical specifications

Atlantic Regional System (Siku)

Located at Memorial University, Siku (meaning “sea ice” in Inuktitut) is a 4500 core computing cluster that incorporates Intel Cascade Lake CPUs, a high-throughput, low-latency EDR Infiniband interconnect, AI-capable NVIDIA Tesla V100 GPUs, a 1.5 PB parallel filesystem, tape back-up, and offers both batch and cloud-computing interfaces.

Meet Siku