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| February,2023 | |
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21 Feb 12:30 pm 2:00 pmIntro to GPU Programming #1An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
22 Feb 9:00 am 10:00 amBCH2202 - Lecture 3In this course students will be instructed in how to program in R. Ultimately students will learn how to use R 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 credit by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
22 Feb 12:30 pm 2:00 pmIntro to GPU Programming #2An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
24 Feb 1:30 pm 3:00 pmIntro to GPU Programming #3An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room | HPC133 - Feb 2023 |
28 Feb 10:30 am 12:00 pmEES1137 Lecture 13In 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 must enrol through Acorn/ROSI. | EES1137 - Winter 2023 |
28 Feb 11:00 am 12:00 pmScientific Computing Lecture (2023)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. | PHY1610 - Winter 2023 |
| March,2023 | |
1 Mar 9:00 am 10:00 amBCH2202 - Lecture 4In this course students will be instructed in how to program in R. Ultimately students will learn how to use R 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 credit by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI. SciNet Teaching Room | BCH2202 - Winter 2023 |
1 Mar 12:00 pm 1:00 pmCO Colloquium "High Performance Computing in R"This week's colloquium: ""High-Performance Computing in R" by Alexey Fedoseev 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 registration is required. Most presentations are recorded and uploaded to the hosting consortium video channel. Virtual | COCO - Mar 2023 |
1 Mar 12:00 pm 1:00 pmCO Colloquium "High Performance Computing in R"This week's colloquium: "Multi-Factor Authentication" by Marco Saldarriaga 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 registration is required. Virtual | COCO - 29 Mar 2023 |
2 Mar 10:00 am 11:30 amEES1137 Lecture 14In 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 must enrol through Acorn/ROSI. | EES1137 - Winter 2023 |

