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December,2023
6 Dec 12:30 pm 2:00 pm

Intro to MPI 2/3

Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems.Format: Virtual Virtual
HPC123 - Dec 2023Show in Google map
8 Dec 12:30 pm 2:00 pm

Intro to MPI 3/3

Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems.Format: Virtual Virtual
HPC123 - Dec 2023Show in Google map
13 Dec 1:00 pm 2:30 pm

Intro to Niagara

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 Virtual
HPC105 - Dec 2023Show in Google map
January,2024
9 Jan 10:00 am 12:00 pm

EES1137: Lecture 1

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 must enrol through Acorn/ROSI.
UTSC: AA207
EES1137 - Winter 2024Show in Google map
9 Jan 11:00 am 12:00 pm

PHY1610 Scientific Computing Lecture

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.
PHY1610 - Winter 2024
10 Jan 1:00 pm 2:30 pm

Intro to Niagara

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 Virtual
HPC105 - Jan 2024Show in Google map
11 Jan 11:00 am 12:00 pm

EES1137: Lecture 2

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 must enrol through Acorn/ROSI.
UTSC: IC120
EES1137 - Winter 2024Show in Google map
11 Jan 11:00 am 12:00 pm

PHY1610 Scientific Computing Lecture

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.
PHY1610 - Winter 2024
15 Jan 1:00 pm 4:00 pm

File Management - Packing Small Files

Managing large amounts of data can be a challenging task. Processing large numbers of files incur heavy overhead of IO communications. This course explores several options such as using Apptainer Overlay and SQLite to pack and reduce a large number of files to few files, and hence, improving IO performance. Python scripts are used throughout the course.Format: Virtual Virtual
DAT171 - Jan 2024Show in Google map
16 Jan 10:00 am 12:00 pm

EES1137: Lecture 3

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 must enrol through Acorn/ROSI.
UTSC: AA207
EES1137 - Winter 2024Show in Google map