Learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP execution and memory model, performance, reductions and load balancing.
Monthly SciNet user meetings, now virtual, with user discussion and a TechTalk. The topic on May 11th, 2022 will be "Modern C++", by Yohai Meiron.
Abstract: C++ has existed for four decades, but has gone through especially significant changes in the 2010s with the advent of the Standard C++11 and beyond. We'll demonstrate some of the new language features, as well as the workflow and tools that make C++ an important programming language for scientific computing, and a lot of fun!
A quick introduction on how to use SciNet and the Niagara and Mist supercomputers.
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. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.
Monthly SciNet user meetings, now virtual, with user discussion and a TechTalk. The topic on April 13, 2022 will be "Data Management on Niagara", by Jaime Pinto.
A quick introduction on how to use SciNet and the Niagara and Mist supercomputers.
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.
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.
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.
Monthly SciNet user meetings, now virtual, with user discussion and a TechTalk. The topic on March 9 2022 will be on "SSH Keys for Niagara" by Raphaelle Gauriau.
SSH keys: really, are you sure you know everything about them?
Let's join us for some fun, interactive session to test and maybe improve your knowledge on SSH keys!
A quick introduction on how to use SciNet and the Niagara and Mist supercomputers.
Working with Advanced Research Computing and High Performance Computing systems involves using the Linux command line. This workshop will cover Linux commands to improve your productivity on the command line.
Monthly SciNet user meetings, now virtual, with user discussion and a TechTalk. The topic on Feb 9 2022 will be on "Using a Database on Niagara", by Yohai Meiron.
Abstract: Niagara has a dedicated node now running a PostgreSQL server for use by researchers. In this talk, we'll discuss the possible uses of a relational database management system, and when it is more appropriate to use a client-server system such as PostgreSQL as opposed to an "embedded" solution like SQLite.
A quick introduction on how to use SciNet and the Niagara and Mist supercomputers.
Working with many of the HPC systems in Ontario 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. This hands on session will cover basic commands. It could be a great boon for your productivity.
A quick introduction on how to use SciNet and the Niagara and Mist supercomputers.
In this course students will be instructed in how to program in Python. Ultimately students will learn how to use Python to analyze, process and visualize data. This course is designed for students with little to no experience in programming.
This is a graduate course that can be taken for by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI.
In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data. Topics include: Python and R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enrol through Acorn/ROSI.
This course is part of the EES graduate program and will be taught online this semester.
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, ...).
