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April,2024
10 Apr 11:00 am 12:00 pm

Intro to Python for Biochemistry

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.
BCH2203 - Winter 2024
10 Apr 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 - Apr 2024Show in Google map
15 Apr 1:00 pm 4:00 pm

Shell Scripting

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.Note: this event has been moved from April 8th to April 15th.Format: Virtual Virtual
SCMP201 - Apr 2024Show in Google map
17 Apr 12:00 pm 1:00 pm

CO Colloquium "How to Buy a Supercomputer for Scientific Computing"

Buying a new supercomputer that both maximises total performance, given our budget, and whose architecture suits our users' workloads is a very difficult balancing act. There are a wide range of decisions to be made, such as: CPU architecture; node count; memory size/bandwidth; GPU count; interconnect type; storage size; filesystem type/bandwidth; cooling type and power budget to name but a few. In order to balance all of these constraints we need to come up with a scoring system to compare potential candidate supercomputers. In this talk we describe the Scalable System Improvement (SSI) metric and apply it to the system refresh of Niagara & Mist. Virtual
COCO - 17 Apr 2024Show in Google map
23 Apr 11:00 am 12:00 pm

DAT112: Lecture 1

Introduction to neural network programming, lecture 1
DAT112 - Apr 2024
25 Apr 11:00 am 12:00 pm

DAT112: Lecture 2

Introduction to neural network programming, lecture 2
DAT112 - Apr 2024
June,2024
7 Jun 1:30 pm 2:50 pm

DAT112: Lecture 3

Virtual
COSS2024Show in Google map
10 Jun 9:00 am 12:00 pm

CO Summer School S2: Introduction to Scalable and Accelerated Data Analytics (session 1/2)

Some popular Python libraries for data analytics, like Numpy, Pandas, Scikit-Learn, etc., usually work well if the dataset fits into the RAM on a single machine. When dealing with large datasets, it could be a challenge to work around memory constraints. This course introduces scalable and accelerated data analytics with Dask and RAPIDS. Dask provides a framework and libraries that can handle large datasets on a single multi-core machine or across multiple machines on a cluster. RAPIDS, on the other hand, can accelerate your data analytics by offloading analytics workloads to GPUs with less effort in code changes. Level: Introductory Length: Two 3-Hour Sessions (2 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic Python and Linux command line experience. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
10 Jun 9:00 am 12:00 pm

CO Summer School S1: Text Mining

This workshop introduces the topic of text mining and its applications. It covers different encoding mechanisms to convert text into numbers that algorithms can handle. It gives an overview of different text mining tasks, including de-identification, sentiment analysis and document clustering, and how they work with examples and live demos. There will also be references to state-of-the-art tools and libraries to conduct various text mining tasks. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic Python (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
10 Jun 1:30 pm 4:30 pm

CO Summer School S2: Reproducible Research - Practices and Tools

Have you ever tried to run someone else’s code and it just didn’t work? Have you ever been lost interpreting your colleague’s data? This hands-on session will provide researchers with tools and techniques to make their research process more transparent and reusable in remote computing environments. You’ll be using platforms like JupyterHub and command-line tools like Bash and Docker in a Linux environment to interact with the material through various exercises and examples. In this workshop, you’ll learn about: organizing your file directories writing readable metadata with README files automating your workflow with scripts capture and share your computational environment Level: Introductory Length: 3 hours Format: Lecture + Hands-on Prerequisites: Initial familiarity with command line tools and/or a Linux environment may be beneficial but not mandatory (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map