What is High Performance Computing (HPC) and what can it do for me? How can ACENET help? Used across many sectors to tackle analyses too large or complex for a desktop, or to achieve improved efficiency over a desktop, this session takes participants through the preliminary stages of learning about high performance computing (HPC) and computing clusters, and how to get started with this type of computing. It then reviews software packages available for applications, data analysis, software development and compiling code. Finally, participants will be introduced to the concept of parallel computing to achieve much faster results in analysis. This session is designed for those with no prior experience in HPC, and are looking for an introduction and overview.

Linux is the terminal interface used to enable you to use supercomputing clusters from your desktop. It's the tool you need to get your data on the clusters, run your programs, and get your data back. In this session, learn how to get started with Linux, how to create and navigate directories for your data, load files, manage your storage, run programs on compute clusters, and set file permissions. This workshop is designed for those with no prior experience in working with a terminal interface.

Shell scripting helps you save time, automate file management tasks, and better use the power of Linux. You’ll learn how to use the command line to carry out repetitive tasks, extract information from files quickly, combine commands in powerful ways, learn about job scripts, shell variables and looping commands, and capture a workflow so you can re-use it easily. Save time, reduce errors, and use Linux more effectively. This workshop is designed for either new High Performance Computing (HPC) users who are familiar with working in a Linux environment, or for experienced users seeking to get more out of shell scripting. It is one of the core courses to help users get up and running on ACENET. Prerequisite: ACENET Basic Series Introduction to Linux, or previous experience with Linux.

The national systems use a job scheduler called “Slurm”. In this session you will learn how Slurm works and how it allocates jobs, helping you to: minimize wait time by framing reasonable requests; ask for only the resources you need, to improve efficiency; increase throughput; run more jobs simultaneously; and troubleshoot and address crashes. This workshop is designed for new HPC users, or for experienced users either transitioning to Slurm or seeking to improve efficiency with the scheduler. Prerequisites: Completion of Introduction to Linux and Introduction to Shell Scripting, or prior experience with both.

Apache Spark is a user-friendly open-source platform for large-scale data processing, analytics and for parallel-computing. Using Apache Spark and Python (PySpark), this workshop is aimed at analyzing data sets that are too large to be handled and processed by a single computer. With hands-on guided examples, the workshop covers the basics of Spark and Resilient Distributed Datasets (RDD) high-level architecture. The examples are mainly written in Python, hence the APIs covered are the ones available in PySpark, including Spark Core API (RDD API), Spark SQL, and Pandas on Spark. Participants will learn how to import data, use functions to transform, reduce and compile the data, and produce parallel algorithms that can run on Alliance clusters. Prerequisites: ACENET Basics or equivalent How to write functions in Python

We all know the advantages of a bar chart instead of a table full of numbers. The bigger your dataset, the greater the value of seeing it visually and being able to pinpoint both broad and specific critical areas for decisions. Scientific visualization of large datasets can be applied across a number of areas, including engineering, material science, sensor/drone data, geospatial, and life sciences. Join them at this session to learn about powering up innovation with supercomputing, and using scientific visualization to make better decisions. There are no prerequisites and no technical knowledge is needed. This session is aimed at mid to senior level managers with R&D technology responsibilities, and R&D engineering or scientific staff with no scientific visualization experience. The webinar is a precursor to the Interactive Data Analysis & Visualization with Paraview workshop below.

Scientific visualization of large datasets allows you to identify critical areas and vulnerabilities during the design process so that you can focus efforts, cut design time and create a better product. This workshop will introduce participants to scientific visualization on both a conceptual and practical level. Following an overview, the session will focus on teaching participants how to use the open-source Paraview visualization software on their own desktop. This will be followed by a demonstration on how open source Paraview can be used on a supercomputer for datasets that are too large for desktop or workstations. This is a beginner, hands-on workshop for R&D engineering or scientific staff with no scientific visualization experience.