HPC clusters

There are multiple HPC clusters with thousands of cores and hundreds of CPUs. They can be used for serial, parallel, GPU and large memory workloads. HPC clusters are configured with a variety of pre-installed software you can use for your research projects. Cluster computing is easy to use and simple to access:

1. Sign in to a shared HPC cluster.
2. Choose the software you want to run.
3. Upload your data onto the cluster. (n.b. or your calculations will not compute)
4. Submit your jobs into a queue and your computations will run when it's your turn.

Use cases

HPC clusters can be used in a wide variety of ways. Many researchers use HPC clusters for batch processing and running computational workloads like:

• artificial intelligence (AI), machine learning (ML) and deep learning
• big data and data mining
• natural language processing (NLP) and text mining
• fluid dynamics simulations
• computational chemistry, particle physics and astrophysics simulations
• weather, land and ocean simulations
• bioinformatics jobs

Similarly, researchers use the clusters for collaboration:

• sharing data within a research group
• data storage and archiving

Examples

• The Owens lab analyzes genomic data of plants and animals. They run software to identify genomic differences between samples and uses alliance resources to assemble genomes for new species.
• The XCITE lab runs large parallel Monte Carlo simulations of medical imaging systems.

Cluster storage

Cluster storage is available for researchers using an Alliance HPC cluster. This type of storage makes your data accessible from the compute resources you're using for your research. It features:

• up to 10TB per research group in long term storage
  • additional storage options available for temporary data and archived data
• automatic nightly backups
• storage in secure data centres in Canada
• HPC cluster computing integration
• support for multiple ways to transfer data
• file sharing options

Self-help resources