Registration is now open for our annual SHARCNET Summer School on Advanced Research Computing . The school is an annual educational event for graduate/undergraduate students, postdocs and researchers who are engaged in compute-intensive research. These schools are free and provide beginner-to-intermediate level courses on a wide range of subjects, from traditional high performance computing (MPI, CUDA) to data science, machine learning, and popular languages (Python, R etc.); they also include domain-specific courses.
This year the School will be run entirely online due to COVID-19 pandemic . It will start on May 25 as a single stream event and will run until Canada Day.
Programme
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Getting Started: The Shell and Scheduler. May 25, 26.
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Modern C++ and Parallel Programming. May 28, 31, June 1.
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Modern Fortran. June 2, 3, 4.
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Python for HPC. June 7, 8, 9.
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CUDA. June 10, 11, 14.
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Parallel Programming with MPI. June 15-17.
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Deep Learning Foundation. June 18, 21.
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Bioinformatics. June 22, 23.
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Parallel Debugging and Profiling. June 24, 25.
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R for Statistical Computing. June 28, 29.
Summer School Registration
Participants need to register to attend the summer school. Registration is per-course, with no limits on the number of courses. All attendees are required to have a Compute Canada account before registering. Compute Canada accounts are free, but one has to be affiliated with a Canadian academic institution to qualify for one. To apply for a Compute Canada account, please follow this link: https://www.computecanada.ca/research-portal/account-management/apply-for-an-account/ . Be aware that it might take a couple of business days to get your account approved.
Once you have a Compute Canada account, you can login to our Training web site using your Compute Canada credentials:
https://training.sharcnet.ca
After that you can follow the link below to register for our Summer School courses:
https://training.sharcnet.ca/course/index.php?categoryid=28
Registration is limited, on a first come, first served basis, so please register early.