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June,2024 | |
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13 Jun 9:00 am 12:00 pmCO Summer School S1: Using Containers: Apptainer (morning session)Apptainer is a secure container technology designed to be used on for high performance compute clusters. This workshop will focus on how to use Apptainer as well as how to make use of tools such as Conda and Spack within Apptainer. By the end of these sessions, one: will have learnt about Apptainer and how it is installed and used on our computer clusters, how to build an Apptainer container image, how to install tools such as Conda/Spack from inside an Apptainer container shell, and, how to use Apptainer containers within job submission scripts. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Experience using Alliance compute clusters, e.g., using the BASH shell and submitting jobs. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024![]() |
13 Jun 9:00 am 12:00 pmCO Summer School S2: Artificial Neural Networks aka Deep Learning (session 2/4)NOTE: This course is divided into four (4) parts over three (3) days. Part I and Part II Description: Introduction of 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 concepts. (The Keras neural network framework will be used for neural network programming but no experience with Keras will be expected.) Part III Description: This part will continue the development of neural network programming approaches from Parts I and II. This part will focus on generative methods used to create images: variational auto-encoders, generative adversarial networks, and diffusion networks. Part IV Description: This part will continue the development of neural network programming approaches from Parts I through III. This part will focus on methods used to generate sequences: LSTM networks, sequence-to-sequence networks, and transformers. Level: Intermediate Length: Four 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Experience with Python (version 3.10) is assumed. Each part assumes what was covered in the previous parts of this course. Parts III and IV assume experience with neural network programming, per the first two neural network programming sessions in this course. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024![]() |
13 Jun 1:30 pm 4:30 pmCO Summer School S1: Using Containers: Apptainer (afternoon session)Apptainer is a secure container technology designed to be used on for high performance compute clusters. This workshop will focus on how to use Apptainer as well as how to make use of tools such as Conda and Spack within Apptainer. By the end of these sessions, one: will have learnt about Apptainer and how it is installed and used on our computer clusters, how to build an Apptainer container image, how to install tools such as Conda/Spack from inside an Apptainer container shell, and, how to use Apptainer containers within job submission scripts. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Experience using Alliance compute clusters, e.g., using the BASH shell and submitting jobs. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024![]() |
13 Jun 1:30 pm 4:30 pmCO Summer School S2: oneAPI library and programming model for image inferencing for both CPU and GPUoneAPI is a unified application programming interface intended to be used across different compute accelerator architectures, including CPUs, GPUs and AI accelerators. It's aim is to unify the programming model as well as simplifying cross-architecture development. It also provides libraries for: deep neural network (DNN) learning applications, collective communications for machine learning and deep learning projects, and, data analytics making big data analysis faster using optimized algorithms. By the end of this workshop one will have: learned about oneAPI libraries and the inference toolkit, components, and capabilities for developing and deploying computer vision and deep learning solutions, explored techniques for optimizing pre-trained deep learning models and learn how to work with models from different frameworks like Tensorflow, PyTorch and Caffe, understood how to perform inference on different hardware such as CPU and GPU, and, considered practical computer vision applications and use cases. Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Attendees having hands-on experience with Python and some experience with Tensorflow or PyTorch will get the most out of this workshop. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024![]() |
March,2025 | |
13 Mar 11:00 am 12:00 pmCO Summer School S1: Machine Learning with MATLABThis 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 2025 |
18 Mar 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
20 Mar 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
25 Mar 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
27 Mar 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
April,2025 | |
1 Apr 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
3 Apr 11:00 am 12:00 pmPHY1610 Scientific Computing LectureThis 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 2025 |
14 Apr 1:00 pm 4:00 pmLinux Shell ScriptingLearn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.Format: Virtual Virtual | SCMP201 - Apr 2025![]() |
22 Apr 1:00 pm 4:00 pmHPC PythonParallel programming in Python. We will cover subprocess, numexpr, multiprocessing, MPI, and other parallel-enabling python packages.Format: Virtual Virtual | HPC111 - Apr 2025![]() |
28 Apr 1:00 pm 4:00 pmParallel Debugging with DDTDebugging 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. Virtual | HPC245 - Apr 2025![]() |
May,2025 | |
5 May 1:00 pm 4:00 pmRelational DatabasesPrinciples 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 Virtual | SCMP231 - May 2025![]() |