| June,2024 |
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| 10 Jun 9:00 am 12:00 pmSome 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 | COSS2024 |
| 10 Jun 9:00 am 12:00 pmThis 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 | COSS2024 |
| 10 Jun 1:30 pm 4:30 pmThis course is intended to help learners with a basic understanding of fluid dynamics and CFD bridge the knowledge gap towards the effective utilization of CFD on modern HPC architectures. This course will take an end-user approach to CFD tools on HPC systems (no coding) and, despite some prerequisites, will be given at an introductory/intermediate level (we will not cover advanced topics such as GPU or dynamic load-balancing). At the end of the course, the learner will be able to: Develop a systematic approach to estimate the HPC cost of a CFD problem. Explain the impact of modelling assumptions on HPC cost. Optimize the parameters and simulations for effective HPC usage. The course will use an entirely open source suite of CFD toolsets to mesh (Gmsh), simulate (OpenFoam/SU2), and visualize (Visit/Paraview). It should be noted that this is not a CFD course; therefore, undergraduate-level knowledge of CFD and numerical methods is expected, as well as a basic understanding of the Compute Ontario HPC system. The focus is on the effective use of CFD tools in modern HPC systems. Level: Intermediate, Length: Three 1-Hour Sessions (3 Days), Format: Lecture + Hands-on, Prerequisites: Undergraduate-level knowledge of fluid dynamics (ideally with some knowledge of turbulence), CFD, and numerical methods. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
| 10 Jun 1:30 pm 4:30 pmHave 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 | COSS2024 |
