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May,2024
7 May 11:00 am 12:00 pm

DAT112: Lecture 5

Introduction to neural network programming, lecture 5
DAT112 - Apr 2024
8 May 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 - May 2024Show in Google map
9 May 11:00 am 12:00 pm

DAT112: Lecture 6

Introduction to neural network programming, lecture 6
DAT112 - Apr 2024
13 May 1:00 pm 4:00 pm

Relational Databases

Principles 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 2024Show in Google map
14 May 11:00 am 12:00 pm

DAT112: Lecture 7

Introduction to neural network programming, lecture 7
DAT112 - Apr 2024
16 May 11:00 am 12:00 pm

DAT112: Lecture 8

Introduction to neural network programming, lecture 8
DAT112 - Apr 2024
21 May 11:00 am 12:00 pm

DAT112: Lecture 9

Introduction to neural network programming, lecture 9
DAT112 - Apr 2024
23 May 11:00 am 12:00 pm

DAT112: Lecture 10

Introduction to neural network programming, lecture 10
DAT112 - Apr 2024
27 May 1:00 pm 4:00 pm

Bash idioms, awk, etc.

This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.Format: Virtual
SCMP281 - May 2024
28 May 11:00 am 12:00 pm

DAT112: Lecture 11

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

DAT112: Lecture 12

Introduction to neural network programming, lecture 12
DAT112 - Apr 2024
June,2024
3 Jun 9:00 am 12:00 pm

CO Summer School S2: Data Preparation

This course provides you with essential knowledge and skills to effectively prepare data for analysis. Starting with an overview of the Data Analytics pipeline and processes, the course explores various statistical and visualization techniques used in Exploratory and Descriptive Analytics to understand historical data. You will then delve into the art of Data Preparation, gaining expertise in data cleaning, handling missing values, detecting, and handling outliers, as well as transforming and engineering features. By the end of the course, you will be equipped with the necessary tools to ensure data quality and integrity, enabling you to make informed decisions and derive valuable insights from their data. 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
3 Jun 9:00 am 12:00 pm

CO Summer School S1: Introduction to Linux shell (morning session)

Running programs on the supercomputers is done via the BASH shell. This course is two three hour live demos on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered. A series of exercises are required to be done in order to complete the course. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
3 Jun 1:30 pm 4:30 pm

CO Summer School S2: Data Security

Be aware. Stay secure. Join us to learn more about the tools you can use to prevent the theft of your data and possibly of your identity. Other topics of discussion will include common hacking attempts, how to recognize them, and how to avoid having your data compromised, stolen, or destroyed. We will also talk about data encryption and provide tips for when travelling with electronic devices. Level: Introductory Length: 3 hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
3 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to Linux shell (afternoon session)

Running programs on the supercomputers is done via the BASH shell. This course is two three hour live demos on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered. A series of exercises are required to be done in order to complete the course. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
4 Jun 9:00 am 12:00 pm

CO Summer School S1: Introduction to Advanced Research Computing

This workshop is a primer for those largely new to supercomputing, i.e., to computing on shared, remote resources. It is intended to demystify the somewhat intimidating term "High-Performance Computing" (HPC), and to serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, available resources, essential issues, and a high level overview of parallel programming models commonly used on these systems. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic Linux e.g. "Introduction to Linux Shell" (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
4 Jun 9:00 am 12:00 pm

CO Summer School S2: Bioinformatics: Analysis of RNA-sequencing data

RNA-Seq refers to high throughput sequencing methods that probes the entire transcriptomic landscape of a given tissue or sample of interest. The data acquired from such experiments can be used to explore the overall RNA profile of a sample as well as comparing samples under various conditions. While extremely powerful, RNA-Seq is susceptible to numerous experimental pitfalls and requires intimate knowledge of the experimental procedures and data analysis methods. When conducted properly RNA-Seq can reveal information about gene/transcript expression, splicing and the effects of mutations. In this session we will take a thorough look at a comprehensive RNA-Seq pipeline, from sample processing methods to final differential expression analysis. Relevant R / BioConductor packages will be introduced. We will have the opportunity to investigate numerous quality control metrics, perform genomic alignment, differential expression and pathway enrichment analysis. We will cover several “gotcha”s and common mistakes in experimental design and data analysis. Basic familiarity with R and Linux command line will be beneficial but not required. All necessary commands and parameters will be explained during the class. Participants will be offered hands-on practice in which they will use RStudio to run R/BioConductor scripts for data analysis as well as the Integrative Genomic Viewer (IGV) software to visualize genomic data on their laptops Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic R and Linux beneficial but not required (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
4 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to Version Control with Git

Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration. This introductory workshop will teach you the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic Linux (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
4 Jun 1:30 pm 4:30 pm

CO Summer School S2: Bioinformatics: Long-read sequencing applications

Long-read sequencing technologies enable the sequencing of DNA fragments 10KB and longer. This read length greatly improves sequence mappability and assembly, providing an advantage over short-read sequences that are difficult to map uniquely to repetitive and GC-rich regions. Long-read sequencing has applications in a number of fields including genome assembly, diagnosis of genetic diseases, and metagenomics. In this workshop, we will focus on PacBio HiFi sequences and introduce you to tools for haplotyping, calling and visualizing structural variants and repeat expansions, visualizing read methylation, and detecting novel isoforms from PacBio Iso-Seq data. Participants will be offered hands-on practice in which they will use RStudio to run R/BioConductor scripts for data analysis as well as the Integrative Genomic Viewer (IGV) software to visualize genomic data on their laptops Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic R (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 9:00 am 10:20 am

CO Summer School S2: Research Data Management: Rationale for Reproducibility

The role of good research data management practices in supporting research reproducibility is becoming increasingly well known. The literature is replete, however, with examples of poor methodology, lack of transparency, mistakes, and misconduct leading to bad science and an inability to reproduce results. This introductory session will provide real-world, illustrative examples of each of these, along with practical suggestions on how to avoid them. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 9:00 am 12:00 pm

CO Summer School S1: Introduction to Python (morning session)

This course is designed to provide you with a solid foundation in Python programming language. Through a comprehensive curriculum and hands-on coding exercises, participants will learn the fundamentals of Python syntax, data types, functions, and file handling. By the end of the course, you will have gained the essential skills to write Python programs, solve problems, and build the foundation for more advanced Python development. Whether you are a beginner or have some programming experience, this course will equip you with the necessary tools to start your journey in Python programming. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 10:30 am 11:50 am

CO Summer School S2: From the I-Ching to ChatGPT: A Brief History of AI and Some Historical and Current Applications

Google's 2017 research paper "Attention Is All You Need" described the transformer, a new machine learning technique. From that paper the modern Large Language Model was born, and we're now living in the thick of a new era brought on by companies like OpenAI, Mistral and Anthropic. But where does this cutting-edge technology come from? What are its roots? What are its problems? This talk explores the history of procedural generation in text and games, from the I-Ching to tranformer-based language models and beyond. The talk will emphasize current state of the art in text-based language models, and include demonstrations on how to run language models locally on your own hardware. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 1:30 pm 2:50 pm

CO Summer School S2: Using generative AI tools for research data management

In this workshop, we will explore the potential uses of generative artificial intelligence tools in research data management (RDM) with a focus on specific use cases. For example, can AI tools be used to write Data Management Plans, summarize funder requirements, assist with data analysis, or suggest file naming conventions and folder structures? This workshop will be interactive, and participants will be welcome to practice using AI tools along with the presenters using real-world data and prompts. We will also discuss the ethical considerations, including benefits and risks, of using AI tools in research and whether it is possible to use AI for RDM practices in an ethical manner. Level: Introductory Length: 1.5 Hours Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to Python (afternoon session)

This course is designed to provide you with a solid foundation in Python programming language. Through a comprehensive curriculum and hands-on coding exercises, participants will learn the fundamentals of Python syntax, data types, functions, and file handling. By the end of the course, you will have gained the essential skills to write Python programs, solve problems, and build the foundation for more advanced Python development. Whether you are a beginner or have some programming experience, this course will equip you with the necessary tools to start your journey in Python programming. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
5 Jun 3:00 pm 4:20 pm

CO Summer School S2: Introduction to Alliance RDM Services

This session provides an overview of the Research Data Management (RDM) Services offered by the Digital Research Alliance of Canada, including the DMP Assistant, a national, bilingual platform for the creation and management of data management plans (DMPs), the Federated Research Data Repository (FRDR), a bilingual publishing platform for sharing and preserving Canadian research data, and Lunaris, Canada’s national discovery service for multidisciplinary data from over 90 academic, government, and research repositories across the country. This session will introduce participants to these platforms and provide an overview of how they support the research lifecycle. Attendees will gain valuable insights into the benefits of these tools and how they can help researchers to streamline their data management workflows. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
6 Jun 9:00 am 12:00 pm

CO Summer School S2: High-Performance I/O and Storage

This workshop will help you understand the relation between storage systems and application-level performance. We will survey the design of storage found on national systems, and consider their performance implications. A range of different IO techniques, data formats, and libraries will be considered. Ideally, participants should have an account on the National Platform (DRI). Level: intermediate, examples/exercises will be in Python; having a DRAC account will be helpful. Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Alliance Account, Python Experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
6 Jun 9:00 am 12:00 pm

CO Summer School S1: AI Showcase

This course introduces Artificial Intelligence (AI), a science focusing on developing intelligent systems capable of autonomous behavior. In this course, we explore the exciting world of AI, introducing its definition and history. We discuss the advantages and challenges of AI in the present time, along with various applications and projects that demonstrate its capabilities. Throughout the session, participants will gain insights into different types of AI, learn about running predefined projects, and discover AI showcases on various platforms. By the end of the course, participants will have the knowledge and resources to start their own AI projects with their data, exploring the latest AI advancements in our clusters. Level: Introductory Length: 3 Hours Format: Lecture Prerequisites: Basic Python beneficial but not required (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
6 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to R

This half-day session offers a brief introduction to R, with a focus on data analysis and statistics. We will discuss the following topics: the R interface, primitive data types, lists, vectors, matrices, and data frames - a crucial data type in data analysis and the trademark of the R language. Advanced topics to be covered include: basics statistics and function creation; *apply family functions; and the basics of scripting. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisite: Some programming experience in another programming language (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
6 Jun 1:30 pm 2:50 pm

CO Summer School S2: Supporting research with Data Management Plans & the DMP Assistant!

This session will provide participants with information, guidance, and resources for supporting research through the development and implementation of data management plans (DMPs). Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None General topics covered will include the importance and benefits of DMPs, their content, and impending DMP requirements relating to the Tri-Agency research data management (RDM) policy. Specific focus will be given to the Digital Research Alliance of Canada DMP Assistant platform that is hosted nationally at the University of Alberta Library, along with a new DMP template developed by the Alliance’s DMP Expert Group (DMPEG). This new template is targeted specifically to support researchers in meeting DMP requirements at the funding opportunity application stage. Additional information relating to an accompanying assessment rubric that is currently in development will be shared. Time will be reserved for questions and discussion. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
6 Jun 3:00 pm 4:20 pm

CO Summer School S2: Empowering Open Science: An Introduction to Depositing and Sharing Research Data and Code in Borealis

The reproducibility of research is essential to the scientific community, as it ensures the accuracy and reliability of research findings that are used to build upon existing knowledge. However, reproducibility is often hindered by the lack of access to research data, documentation, and code. This workshop will provide an overview of the concepts of open science, reproducibility, and the FAIR principles of research data, as well as explore how to deposit and share data in Borealis, the Canadian Dataverse Repository, a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. Level: Introductory; Length: 1.5 Hours; Format: Lecture; Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
7 Jun 9:00 am 10:20 am

CO Summer School S2: Academic Libraries and Machine Learning: Transforming the Library

The application of machine learning (ML) to academic libraries promises to be transformational. A Task Force of the Ontario Council of University Libraries (OCUL) has been exploring this technology and identifying specific ML use cases. OCUL is an association of the 21 university libraries in Ontario who collaborate on many shared services and resources. This session will review the work of the Task Force with a focus on use cases, and the requirements and processes to implement pilot programs and production services. Particular attention will be placed on the technology infrastructure (compute, software) and the expertise requirements (technology, domain). Use cases to be discussed include audio to text transcription, metadata creation, virtual reference (chat), and discovery using natural language processing (NLP), semantic search, and summarization. The discovery use case will be applied to some of the extensive data collections maintained by Scholar Portal, the shared resource managed by OCUL, including over 65 million articles from over 27,000 full text scholarly journals and a collection of over 800K digital books and government documents. Participants will be encouraged to engage with key questions about the adoption and use of machine learning in libraries and to provide feedback on the ongoing evolution of this technology as it benefits library applications. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
7 Jun 9:00 am 12:00 pm

CO Summer School S1: Introduction to C (morning session)

This course will provide hands-on experience on fundamental concepts of programming using C. This will include Conditional statement, Loops(while and for), Arrays, Pointers, Functions and Dynamic memory allocation. An introduction will be provided regarding fundamental data structures such as linked list, stacks, queues and binary trees. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
7 Jun 1:30 pm 2:50 pm

CO Summer School S2: Working with Jupyter on the clusters

Jupyter Notebook is commonly used for interactive computing in Python. This session provides the options and features for working with Jupyter on the Digital Research Alliance of Canada's remote computing clusters and demonstrates several use case examples on the clusters. Level: Introductory Length: 1.5 Hours Format: Lecture + Demonstration Prerequisites: Basic Python and Linux command line experience. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
7 Jun 1:30 pm 4:30 pm

CO Summer School S1: Introduction to C (afternoon session)

This course will provide hands-on experience on fundamental concepts of programming using C. This will include Conditional statement, Loops(while and for), Arrays, Pointers, Functions and Dynamic memory allocation. An introduction will be provided regarding fundamental data structures such as linked list, stacks, queues and binary trees. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
7 Jun 3:00 pm 4:20 pm

CO Summer School S2: Using Odesi for Survey and Public Opinion Research

Odesi (odesi.ca) is a Canadian social science data repository and online data exploration and analysis tool. Odesi’s collections include over 5,700 historical and contemporary surveys and public opinion polls from a variety of data providers such as Statistics Canada and the Canadian Opinion Research Archive (CORA). This workshop will demonstrate how to effectively search for and access data within Odesi on a variety of social, economic, and political topics. Attendees will learn how to navigate the interface, using search features and available collections, explore survey questions (variables), perform basic tabulations and analysis using connected tools, and download datasets into statistical software (e.g. R, SPSS) for further analysis. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (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 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 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
10 Jun 1:30 pm 4:30 pm

CO Summer School S1: Leveraging HPC for Computational Fluid Dynamics (session 1/3)

This 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
COSS2024Show in Google map
11 Jun 9:00 am 12:00 pm

CO Summer School S2: Machine Learning (morning session)

This course provides an introduction to machine learning that enables computers to learn AI models from data without being explicitly programmed. It comprises two parts: Part I covers the fundamentals of machine learning, and, Part II demonstrates the applications of various machine methods in solving a real world problem. Rather than presenting the key concepts and components of machine learning in an abstract way, this course introduces them with a small number of examples. By using plotting and animations, insight into some of the mechanics of machine learning can be had. Furthermore, the student will gain practical skills in a case study, in which each step of developing a machine learning project is presented. By the end of this course, the student will have a solid understanding and experience with some of the fundamentals of machine learning enabling subsequent exploration. Level: Introductory to Intermediate Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Alliance Account Data preparation or equivalent knowledge. Basic Python knowledge and experience. Knowledge and experience with Tensorflow and Scikit-learn would also be helpful. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
11 Jun 9:00 am 12:00 pm

CO Summer School S1: Multicore parallel programming (OpenMP) (morning session)

This is an introduction to the intermediate level OpenMP hand-on course. OpenMP is a standard parallel programming API that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran. This one-day course will cover the principles of OpenMP compiler directives, library routines, and environment variables with step-by-step hand-on examples. Case studies include various approaches for loop parallelism. We will also talk about the Task constructs for irregular programs, and the Target constructs for accelerators such as GPU. Participants will have hand-on programming experience with OpenMP as well as how to compile and run Multi-thread OpenMP code on different alliance clusters. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on (Hands-on portion is CPU only.) Prerequisites: Basic knowledge of C, C++, or Fortran (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
11 Jun 1:30 pm 4:30 pm

CO Summer School S1: Multicore parallel programming (OpenMP) (afternoon session)

This is an introduction to the intermediate level OpenMP hand-on course. OpenMP is a standard parallel programming API that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran. This one-day course will cover the principles of OpenMP compiler directives, library routines, and environment variables with step-by-step hand-on examples. Case studies include various approaches for loop parallelism. We will also talk about the Task constructs for irregular programs, and the Target constructs for accelerators such as GPU. Participants will have hand-on programming experience with OpenMP as well as how to compile and run Multi-thread OpenMP code on different alliance clusters. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on (Hands-on portion is CPU only.) Prerequisites: Basic knowledge of C, C++, or Fortran (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
11 Jun 1:30 pm 4:30 pm

CO Summer School S2: Machine Learning (afternoon session)

This course provides an introduction to machine learning that enables computers to learn AI models from data without being explicitly programmed. It comprises two parts: Part I covers the fundamentals of machine learning, and, Part II demonstrates the applications of various machine methods in solving a real world problem. Rather than presenting the key concepts and components of machine learning in an abstract way, this course introduces them with a small number of examples. By using plotting and animations, insight into some of the mechanics of machine learning can be had. Furthermore, the student will gain practical skills in a case study, in which each step of developing a machine learning project is presented. By the end of this course, the student will have a solid understanding and experience with some of the fundamentals of machine learning enabling subsequent exploration. Level: Introductory to Intermediate Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Alliance Account Data preparation or equivalent knowledge. Basic Python knowledge and experience. Knowledge and experience with Tensorflow and Scikit-learn would also be helpful. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
12 Jun 9:00 am 12:00 pm

CO Summer School S1: Parallel Computing with MATLAB

During this hands-on workshop, we will introduce parallel and distributed computing in MATLAB with a focus on speeding up application codes and offloading compute. By working through common scenarios and workflows using hands-on demos, you will gain a detailed understanding of the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you'll encounter when using them. Users will learn: Multithreading vs multiprocessing When to use parfor vs parfeval constructs Creating data queues for data transfer Leveraging NVIDIA GPUs Parallelizing Simulink models Working with large data Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Working knowledge of MATLAB (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
12 Jun 9:00 am 12:00 pm

CO Summer School S2: Artificial Neural Networks aka Deep Learning (session 1/4)

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
COSS2024Show in Google map
12 Jun 1:00 pm 2:30 pm

CANCELED: 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.THIS EVENT HAS BEEN CANCELED. Virtual
HPC105 - Jun 2024Show in Google map
12 Jun 1:30 pm 4:30 pm

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

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
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12 Jun 1:30 pm 4:30 pm

CO Summer School S1: Leveraging HPC for Computational Fluid Dynamics (session 2/3)

This 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
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13 Jun 9:00 am 12:00 pm

CO 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
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13 Jun 9:00 am 12:00 pm

CO 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
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13 Jun 1:30 pm 4:30 pm

CO 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
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13 Jun 1:30 pm 4:30 pm

CO Summer School S2: oneAPI library and programming model for image inferencing for both CPU and GPU

oneAPI 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
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14 Jun 9:00 am 12:00 pm

CO Summer School S1: Machine Learning with MATLAB

Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. In this hands-on introductory workshop, you will learn how to apply Machine Learning, and get familiar with the basics of Deep Learning. MATLAB provides an environment to apply advanced techniques without requiring extensive coding nor experience in machine learning. Learn the fundamentals of machine learning (supervised learning, feature extraction, and hyperparameter tuning) Explore pre-processing and powerful visualization techniques Build and evaluate machine learning models for classification and regression of various data formats (signals, images, text) Perform hyperparameter tuning and feature selection to optimize model performance Discuss interoperability with other platforms Learn how to deploy Machine Learning models Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Working knowledge of MATLABMachine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. In this hands-on introductory workshop, you will learn how to apply Machine Learning, and get familiar with the basics of Deep Learning. MATLAB provides an environment to apply advanced techniques without requiring extensive coding nor experience in machine learning. Learn the fundamentals of machine learning (supervised learning, feature extraction, and hyperparameter tuning) Explore pre-processing and powerful visualization techniques Build and evaluate machine learning models for classification and regression of various data formats (signals, images, text) Perform hyperparameter tuning and feature selection to optimize model performance Discuss interoperability with other platforms Learn how to deploy Machine Learning models Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Working knowledge of MATLAB (part of the 2024 Compute Ontario Summer School) Virtual
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14 Jun 9:00 am 12:00 pm

CO Summer School S2: Artificial Neural Networks aka Deep Learning (session 3/4)

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
COSS2024Show in Google map
14 Jun 1:30 pm 4:30 pm

CO Summer School S1: Leveraging HPC for Computational Fluid Dynamics (session 3/3)

This 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
COSS2024Show in Google map
14 Jun 1:30 pm 4:30 pm

CO Summer School S2: Artificial Neural Networks aka Deep Learning (session 4/4)

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
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17 Jun 9:00 am 12:00 pm

CO Summer School S1: GPU programming: CUDA (day 1, morning session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
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17 Jun 9:00 am 12:00 pm

CO Summer School S2: High Performance Computing in Python (morning session)

Learn how to improve the performance and use parallel programming in Python. We will cover profiling, subprocess, numexpr, multiprocessing, MPI, and other performance enhancing techniques. Level: Intermediate Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisite: Some Python and Linux command line experience. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
17 Jun 1:30 pm 4:30 pm

CO Summer School S1: GPU programming: CUDA (day 1, afternoon session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
17 Jun 1:30 pm 4:30 pm

CO Summer School S2: High Performance Computing in Python (afternoon session)

Learn how to improve the performance and use parallel programming in Python. We will cover profiling, subprocess, numexpr, multiprocessing, MPI, and other performance enhancing techniques. Level: Intermediate Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisite: Some Python and Linux command line experience. (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
18 Jun 9:00 am 12:00 pm

CO Summer School S2: Modern C++ Parallel Programming (day 1, morning session)

Modern C++ is an efficient, versatile programming language. This workshop will focus on the following in both sequential and parallel contexts: using pseudo-random number generators, making use of reduction options using underlying sequential code, making simple use of in-situ code benchmarking/profiling, and, using mdspan for accessing multi-dimensional arrays and multi-dimensional array slices (submdspan). By the end of these sessions, one will have learnt about sequential and parallel uses of: C++ pseudo-random number generators and their use, C++ std::reduce(), std::transform_reduce(), etc. and C++ parallel algorithms and some of their uses and caveats, using std::chrono facilities, e.g., for in-situ benchmarks, and, how to use multi-dimensional arrays and slices in C++ code. Level: Intermediate Length: Four 3-Hour Sessions (2 Days) Format: Lecture + Hands-on Prerequisites: Experience developing sequential code in C++. (The C++ programming language is not the C programming language. Experience is expected programming in C++, e.g., using the standard library's containers, iterators, and algorithms.) (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
18 Jun 9:00 am 12:00 pm

CO Summer School S1: GPU programming: CUDA (day 2, morning session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
18 Jun 1:30 pm 4:30 pm

CO Summer School S1: GPU programming: CUDA (day 2, afternoon session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
18 Jun 1:30 pm 4:30 pm

CO Summer School S2: Modern C++ Parallel Programming (day 1, afternoon session)

Modern C++ is an efficient, versatile programming language. This workshop will focus on the following in both sequential and parallel contexts: using pseudo-random number generators, making use of reduction options using underlying sequential code, making simple use of in-situ code benchmarking/profiling, and, using mdspan for accessing multi-dimensional arrays and multi-dimensional array slices (submdspan). By the end of these sessions, one will have learnt about sequential and parallel uses of: C++ pseudo-random number generators and their use, C++ std::reduce(), std::transform_reduce(), etc. and C++ parallel algorithms and some of their uses and caveats, using std::chrono facilities, e.g., for in-situ benchmarks, and, how to use multi-dimensional arrays and slices in C++ code. Level: Intermediate Length: Four 3-Hour Sessions (2 Days) Format: Lecture + Hands-on Prerequisites: Experience developing sequential code in C++. (The C++ programming language is not the C programming language. Experience is expected programming in C++, e.g., using the standard library's containers, iterators, and algorithms.) (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
19 Jun 9:00 am 12:00 pm

CO Summer School S2: Scientific visualization (morning session)

During this workshop, we will learn about matplotlib which is a popular Python library that is great for 2D visualizations, and ParaView, a free and open-source visualization tool for creating 3D visualizations of your datasets. In this interactive workshop you will get familiar with how ParaView works and at the end you should be able to generate basic visualizations of the demo data. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
19 Jun 9:00 am 12:00 pm

CO Summer School S1: GPU programming: CUDA (day 3, morning session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
19 Jun 1:30 pm 4:30 pm

CO Summer School S2: Scientific visualization (afternoon session)

During this workshop, we will learn about matplotlib which is a popular Python library that is great for 2D visualizations, and ParaView, a free and open-source visualization tool for creating 3D visualizations of your datasets. In this interactive workshop you will get familiar with how ParaView works and at the end you should be able to generate basic visualizations of the demo data. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
19 Jun 1:30 pm 4:30 pm

CO Summer School S1: GPU programming: CUDA (day 3, afternoon session)

This is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. Level: Introductory Length: Six 3-Hour Sessions (3 Days) Format: Lecture + Hands-on Prerequisites: Alliance Account Basic C and/or C++ experience (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
20 Jun 9:00 am 12:00 pm

CO Summer School S2: Modern C++ Parallel Programming (day 2, morning session)

Modern C++ is an efficient, versatile programming language. This workshop will focus on the following in both sequential and parallel contexts: using pseudo-random number generators, making use of reduction options using underlying sequential code, making simple use of in-situ code benchmarking/profiling, and, using mdspan for accessing multi-dimensional arrays and multi-dimensional array slices (submdspan). By the end of these sessions, one will have learnt about sequential and parallel uses of: C++ pseudo-random number generators and their use, C++ std::reduce(), std::transform_reduce(), etc. and C++ parallel algorithms and some of their uses and caveats, using std::chrono facilities, e.g., for in-situ benchmarks, and, how to use multi-dimensional arrays and slices in C++ code. Level: Intermediate Length: Four 3-Hour Sessions (2 Days) Format: Lecture + Hands-on Prerequisites: Experience developing sequential code in C++. (The C++ programming language is not the C programming language. Experience is expected programming in C++, e.g., using the standard library's containers, iterators, and algorithms.) (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
20 Jun 9:00 am 12:00 pm

CO Summer School S1: Databases and SQL (day 1, morning session)

In our digitally-driven world, databases are the cornerstone of virtually every online service and application. They help store your favourite songs on music platforms, track orders on shopping sites, and keep your personal information safe and sound. These incredible systems are the backbone of our digital universe, silently and efficiently managing the vast oceans of data that flow through our daily lives. From the social media sites we share with our friends to the online transactions that make our lives easier, databases are the unsung heroes, diligently organizing, storing, and retrieving information with remarkable precision. Whether you're a technical professional or just beginning to explore data management, the journey into the realm of databases is both enlightening and rewarding, offering endless opportunities for discovery and innovation. Together, we will explore the secrets that make our connected world tick. Level: Introductory Length: Four 3-Hour Sessions (2 Days) Format: Lecture+Hands-on Prerequisites: Basic programming knowledge Installation of MySQL on one's personal computer (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
20 Jun 1:30 pm 4:30 pm

CO Summer School S1: Databases and SQL (day 1, afternoon session)

In our digitally-driven world, databases are the cornerstone of virtually every online service and application. They help store your favourite songs on music platforms, track orders on shopping sites, and keep your personal information safe and sound. These incredible systems are the backbone of our digital universe, silently and efficiently managing the vast oceans of data that flow through our daily lives. From the social media sites we share with our friends to the online transactions that make our lives easier, databases are the unsung heroes, diligently organizing, storing, and retrieving information with remarkable precision. Whether you're a technical professional or just beginning to explore data management, the journey into the realm of databases is both enlightening and rewarding, offering endless opportunities for discovery and innovation. Together, we will explore the secrets that make our connected world tick. Level: Introductory Length: Four 3-Hour Sessions (2 Days) Format: Lecture+Hands-on Prerequisites: Basic programming knowledge Installation of MySQL on one's personal computer (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
20 Jun 1:30 pm 4:30 pm

CO Summer School S2: Modern C++ Parallel Programming (day 2, afternoon session)

Modern C++ is an efficient, versatile programming language. This workshop will focus on the following in both sequential and parallel contexts: using pseudo-random number generators, making use of reduction options using underlying sequential code, making simple use of in-situ code benchmarking/profiling, and, using mdspan for accessing multi-dimensional arrays and multi-dimensional array slices (submdspan). By the end of these sessions, one will have learnt about sequential and parallel uses of: C++ pseudo-random number generators and their use, C++ std::reduce(), std::transform_reduce(), etc. and C++ parallel algorithms and some of their uses and caveats, using std::chrono facilities, e.g., for in-situ benchmarks, and, how to use multi-dimensional arrays and slices in C++ code. Level: Intermediate Length: Four 3-Hour Sessions (2 Days) Format: Lecture + Hands-on Prerequisites: Experience developing sequential code in C++. (The C++ programming language is not the C programming language. Experience is expected programming in C++, e.g., using the standard library's containers, iterators, and algorithms.) (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
21 Jun 9:00 am 12:00 pm

CO Summer School S1: Databases and SQL (day 2, morning session)

In our digitally-driven world, databases are the cornerstone of virtually every online service and application. They help store your favourite songs on music platforms, track orders on shopping sites, and keep your personal information safe and sound. These incredible systems are the backbone of our digital universe, silently and efficiently managing the vast oceans of data that flow through our daily lives. From the social media sites we share with our friends to the online transactions that make our lives easier, databases are the unsung heroes, diligently organizing, storing, and retrieving information with remarkable precision. Whether you're a technical professional or just beginning to explore data management, the journey into the realm of databases is both enlightening and rewarding, offering endless opportunities for discovery and innovation. Together, we will explore the secrets that make our connected world tick. Level: Introductory Length: Four 3-Hour Sessions (2 Days) Format: Lecture+Hands-on Prerequisites: Basic programming knowledge Installation of MySQL on one's personal computer (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
21 Jun 9:00 am 12:00 pm

CO Summer School S2: Bioinformatics - Introduction and Metagenomics (morning session)

Bioinformatics, the interdisciplinary field at the intersection of biology and computational science, has revolutionized our understanding of life processes. In this one-day course, we will first tune your HPC knowledge/skills towards bioinformatics computing. Then a typical metagenomics pipeline will be explored to introduce common tools used in bioinformatic analysis and to show how they can be run in an HPC environment. Join us for an immersive day of hands-on exploration in the captivating world of bioinformatics and metagenomics! Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Alliance Account Basic understanding of biology and familiarity with Unix shells (e.g. bash, zsh, etc.). (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
21 Jun 1:30 pm 4:30 pm

CO Summer School S2: Bioinformatics - Introduction and Metagenomics (afternoon session)

Bioinformatics, the interdisciplinary field at the intersection of biology and computational science, has revolutionized our understanding of life processes. In this one-day course, we will first tune your HPC knowledge/skills towards bioinformatics computing. Then a typical metagenomics pipeline will be explored to introduce common tools used in bioinformatic analysis and to show how they can be run in an HPC environment. Join us for an immersive day of hands-on exploration in the captivating world of bioinformatics and metagenomics! Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: Alliance Account Basic understanding of biology and familiarity with Unix shells (e.g. bash, zsh, etc.). (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
21 Jun 1:30 pm 4:30 pm

CO Summer School S1: Databases and SQL (day 2, afternoon session)

In our digitally-driven world, databases are the cornerstone of virtually every online service and application. They help store your favourite songs on music platforms, track orders on shopping sites, and keep your personal information safe and sound. These incredible systems are the backbone of our digital universe, silently and efficiently managing the vast oceans of data that flow through our daily lives. From the social media sites we share with our friends to the online transactions that make our lives easier, databases are the unsung heroes, diligently organizing, storing, and retrieving information with remarkable precision. Whether you're a technical professional or just beginning to explore data management, the journey into the realm of databases is both enlightening and rewarding, offering endless opportunities for discovery and innovation. Together, we will explore the secrets that make our connected world tick. Level: Introductory Length: Four 3-Hour Sessions (2 Days) Format: Lecture+Hands-on Prerequisites: Basic programming knowledge Installation of MySQL on one's personal computer (part of the 2024 Compute Ontario Summer School) Virtual
COSS2024Show in Google map
July,2024
8 Jul 12:00 pm 3:00 pm

Intro to Quantum Computing, Lecture 1

This course will provide an introduction to the theory, formalisms and algorithms of quantum computing.  The programming language will be Python; experience with Python will be assumed.  Experience with quantum mechanics is not necessary; an introductory-level understanding of linear algebra will be assumed.This will be an in-person course, July 8 - 12, 12:00 - 3:00pm.This course has been cancelled due to lack of attendance. SciNet Teaching Room
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