Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.
Format: Virtual
Date: Fri, 25 Oct 2024 - 1:00 pm
Scientific Computing Credits: 3
SciNet Education Site
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Welcome to the Education Site for SciNet, the High Performance Computing Consortium at the University of Toronto. Here you will find the course materials for all the classes and courses taught by SciNet.
Our training covers many topics in Research Computing and Data Science, in a variety of forms, such as webinars, workshops, and multi-week courses. Some events are online, while others are in-person, but many of the latter are also broadcast and recorded.
A full catalogue of past and present courses is available here. Access to slides and recordings is open to anyone, but to register for courses and to work towards a SciNet certificate, login is required. Apart from the University of Toronto graduate courses in the list, all training events are free of charge.
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Available courses
Learn how to fully utilize the power of HPC. Discover proven strategies and tools to efficiently scale up from serial jobs to parallel runs across many compute nodes on Niagara.
Date: Mon, 28 Oct 2024 - 1:00 pm
High Performance Computing Credits: 3
New to programming? Learn the basics of programming using python in eight one-hour sessions over the course of four weeks. Sessions will consist of a mix of lectures and hands-on exercises.
Format: In-person. Sessions will be recorded.
Start date: 5 Nov 2024
End date: 5 Dec 2024
Scientific Computing Credits: 8
Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration. In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.
Format: Virtual
Date: Wed, 6 Nov 2024 - 1:00 pm
Data Science Credits: 3
Working with many of the HPC systems (like those at SciNet) involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course which will cover basic commands. It could be a great boon for your productivity.
Format: Virtual
Date: Mon, 25 Nov 2024 - 1:00 pm
Scientific Computing Credits: 3
Container computing is gradually changing the way researchers are developing, sharing, and running software applications. Apptainer (formerly called Singularity) is gaining popularity in HPC for its performance, ease of use, portability, and security. In this course, we will explore: what is a container, why use a container, and how to use and create one.
Format: Virtual
Date: Fri, 29 Nov 2024 - 1:00 pm
Scientific Computing Credits: 3
An introduction to concepts and techniques in parallel computing with compiled languages, e.g., C, C++ or Fortran. Both OpenMP and MPI will be introduced.
Format: Virtual
Start date: 2 Dec 2024
End date: 6 Dec 2024
High Performance Computing Credits: 4
This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).
This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
This is an in-person course.
Start date: 7 Jan 2025
End date: 11 Apr 2025
Scientific Computing Credits: 28
High Performance Computing Credits: 8
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.
Format: Virtual
Date: Mon, 20 Jan 2025 - 1:00 pm
Scientific Computing Credits: 3
This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.
Format: Virtual
Time: 1:00 pm - 4:00 pm EST
Date: Mon, 3 Feb 2025 - 1:00 pm
Scientific Computing Credits: 3
Working with many of the HPC systems (like those at SciNet) involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course which will cover basic commands. It could be a great boon for your productivity.
Format: Virtual
Date: Mon, 3 Mar 2025 - 1:00 pm
Scientific Computing Credits: 3
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.
Format: Virtual
Date: Mon, 14 Apr 2025 - 1:00 pm
Scientific Computing Credits: 3
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.
Classes will be held, April 22 - May 29, 2025, Tuesdays and Thursdays, 11:00am - 12:00pm.
Format: Virtual
Start date: 22 Apr 2025
End date: 29 May 2025
Data Science Credits: 16
Parallel programming in Python. We will cover subprocess, numexpr, multiprocessing, MPI, and other parallel-enabling python packages.
Format: Virtual
Date: Tue, 22 Apr 2025 - 1:00 pm
High Performance Computing Credits: 3
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this session, we will discuss the debugging of frequently encountered bugs in serial code and debugging of parallel (MPI and threaded) codes using DDT.
Date: Mon, 28 Apr 2025 - 1:00 pm
High Performance Computing Credits: 3
Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.
Prerequisites: Some Linux command line experience. Python experience is strongly advised.
Format: Virtual
Date: Mon, 5 May 2025 - 1:00 pm
Data Science Credits: 3
Did you know the Linux operating system has built-in tools to control which specific users and groups can access which files and directories? In this session, you will learn what these Linux permissions are, how to use the available tools to control access and sharing, and how to avoid common security pitfalls.
Date: Fri, 4 Oct 2024 - 1:00 pm
Scientific Computing Credits: 2
The Toronto Bioinformatics Hackathon is a student-led computational biology hackathon, bringing together early career bioinformaticians, molecular biologists, statisticians, and computer scientists from Toronto’s Discovery District to complete interdisciplinary projects that emphasize computational and entrepreneurial thinking.
In partnership with the Terrence Donnelly Centre and the Temerty Faculty of Medicine's Computational Biology in Molecular Genetics program, our participants will collaborate to propose innovative solutions to key challenges in computational biology with commercialization potential.
Start date: 27 Sep 2024
End date: 29 Sep 2025
Scientific Computing Credits: 0
An introduction to basic concepts in High-Performance Computing (HPC). This is intended to be a high-level primer for those largely new to HPC. Topic will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism and a high-level overview of parallel programming models.
Format: Virtual
Start date: 23 Sep 2024
End date: 27 Sep 2024
High Performance Computing Credits: 4
Working with many of the HPC systems (like those at SciNet) involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course which will cover basic commands. It could be a great boon for your productivity.
Format: Virtual
Date: Mon, 16 Sep 2024 - 1:00 pm
Scientific Computing Credits: 3
The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 10:00-11:30am, in VC323.
Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program.
Start date: 10 Sep 2024
End date: 28 Nov 2024
Scientific Computing Credits: 8
Data Science Credits: 28
At your own pace, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.
Date: Tue, 30 Jul 2024 - 12:00 am
High Performance Computing Credits: 2
This course will provide an introduction to the theory, formalisms and algorithms of quantum computing. The programming language will be Python; experience with Python will be assumed. Experience with quantum mechanics is not necessary; an introductory-level understanding of linear algebra will be assumed.
This will be an in-person course, July 8 - 12, 12:00 - 3:00pm.
This course has been cancelled due to lack of attendance.
Date: Mon, 8 Jul 2024 - 12:00 pm
Scientific Computing Credits: 15
In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.
THIS EVENT HAS BEEN CANCELED.
Date: Wed, 12 Jun 2024 - 1:00 pm
High Performance Computing Credits: 1
We are excited to announce the dates for this year’s 2024 Compute Ontario Summer School.
Jointly organized by the Centre for Advanced Computing, SciNet, SHARCNET, and in collaboration with the RDM Network of Experts, this year’s virtual event will be held on June 3-21.
The Compute Ontario Summer School offers a comprehensive curriculum packed with around 40 free courses. Delivered by experts in the field, these sessions cover a wide range of topics including Advanced Research Computing (ARC), High Performance Computing (HPC), and Research Data Management (RDM). With presentations and workshops available at introductory to advanced levels, there is something for everyone.
Registration opened May 15.
Start date: 3 Jun 2024
End date: 21 Jun 2024
This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.
Format: Virtual
Date: Mon, 27 May 2024 - 1:00 pm
Scientific Computing Credits: 3
Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.
Prerequisites: Some Linux command line experience. Python experience is strongly advised.
Format: Virtual
Date: Mon, 13 May 2024 - 1:00 pm
Data Science Credits: 3
In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.
Format: Virtual
Date: Wed, 8 May 2024 - 1:00 pm
High Performance Computing Credits: 1
This week's colloquium: "C++20 Modules" by Ramses van Zon from SciNet.
The Compute Ontario Colloquia are weekly Zoom presentations on Advanced Research Computing, High Performance Computing, Research Data Management, and Research Software topics, delivered by staff from three Compute Ontario consortia (CAC, SciNet, SHARCNET) and guest speakers. The colloquia are one hour long and include time for questions. No enrollment or registration is required. Most presentations are recorded and uploaded to the hosting consortium video channel.
Date: Wed, 1 May 2024 - 12:00 pm
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.
Classes will be held, April 23 - May 30, Tuesdays and Thursdays, 11:00am - 12:00pm.
Format: Virtual
Start date: 23 Apr 2024
End date: 30 May 2024
Data Science Credits: 16