HPC University
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A comprehensive list of training resources from the HPC University. HPCU is a virtual organization whose primary goal is to provide a cohesive, persistent, and sustainable on-line environment to share educational and training materials for a continuum of high performance computing environments that span desktop computing capabilities to the highest-end of computing facilities offered by HPC centers.
An Introduction to Cryptography with Python
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This comprehensive workshop is designed to guide participants through the world of cryptography, from foundational concepts to advanced implementations. Starting with the basics of encryption, decryption, and hashing, the workshop discusses real-world applications like SSL, blockchain, and digital signatures. Interactive Python-based coding examples, such as symmetric and asymmetric encryption, will provide hands-on experience. Participants will also learn to identify cryptographic vulnerabilities and perform attacks like length extension. Finally, the workshop also explores future trends such as quantum cryptography and zero-knowledge proofs, providing participants with the knowledge to apply cryptography in securing modern digital systems. Ideal for beginners and intermediate learners alike, this workshop is a step-by-step journey into mastering cryptographic principles and practices.
Tutorial: Localized RAG Chatbot with ACCESS HPC
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This tutorial shows how to set up an open-source customizable RAG chatbot to answer questions about documents you can choose. It uses Indiana's Jetstream 2 HPC, but should work on any major ACCESS HPC.
Introduction to Python for Digital Humanities and Computational Research
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This documentation contains introductory material on Python Programming for Digital Humanities and Computational Research. This can be a go-to material for a beginner trying to learn Python programming and for anyone wanting a Python refresher.
Gentle Introduction to Programming With Python
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This course from MIT OpenCourseWare (OCW) covers very basic information on how to get started with programming using Python. Lectures are available, along with practice assignments, to users at no cost. Python has many applications in tech today, from web frameworks to machine learning. This course will also instruct users on how to get set up with an IDE, which will allow for way more efficient debugging.
Cornell Virtual Workshop
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Cornell Virtual Workshop is a comprehensive training resource for high performance computing topics. The Cornell University Center for Advanced Computing (CAC) is a leader in the development and deployment of Web-based training programs. Our Cornell Virtual Workshop learning platform is designed to enhance the computational science skills of researchers, accelerate the adoption of new and emerging technologies, and broaden the participation of underrepresented groups in science and engineering. Over 350,000 unique visitors have accessed Cornell Virtual Workshop training on programming languages, parallel computing, code improvement, and data analysis. The platform supports learning communities around the world, with code examples from national systems such as Frontera, Stampede2, and Jetstream2.
Using Linux commands in a python script (and the difference between the subprocess and os python modules)
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Learn how to use Linux commands in a python script. Specifically, learn how to use the subprocess and os modules in python to run shell commands (which run Linux commands) in a python script that is run on a cluster.
Data Visualization tools for Python
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Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It makes analyzing and presenting your data extremely easy and works with Python which many people already know.
DeapSECURE – Data-Enabled Advanced Computational Training Platform for Cybersecurity Research and Education
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DeapSECURE is a training program to infuse high-performance computational techniques into cybersecurity research and education. It is an NSF-funded project of the ODU School of Cybersecurity along with the Department of Electrical and Computer Engineering and the Information Technology Services at ODU. The DeapSECURE team has developed six non-degree training modules to expose cybersecurity students to advanced CI platforms and techniques rooted in big data, machine learning, neural networks, and high-performance programming. Techniques taught in DeapSECURE workshops are rather general and transferable to other areas including science, engineering, finance, linguistics, etc. All lesson materials are made available as open-source educational resources.
NCSA HPC Training Moodle
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Self-paced tutorials on high-end computing topics such as parallel computing, multi-core performance, and performance tools. Other related topics include 'Cybersecurity for End Users' and 'Developing Webinar Training.' Some of the tutorials also offer digital badges. Many of these tutorials were previously offered on CI-Tutor. A list of open access training courses are provided below.
Parallel Computing on High-Performance Systems
Profiling Python Applications
Using an HPC Cluster for Scientific Applications
Debugging Serial and Parallel Codes
Introduction to MPI
Introduction to OpenMP
Introduction to Visualization
Introduction to Performance Tools
Multilevel Parallel Programming
Introduction to Multi-core Performance
Using the Lustre File System
Spatial Data Science in the Cloud (Alpine HPC) using Python
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Spatial Data Science is a growing field across a wide range of industries and disciplines. The open-source programming language Python has many libraries that support spatial analysis, but what do you do when your computer is unable to tackle the massive file sizes of high-resolution data and the computing power required in your analysis?
There materials have been prepared to teach you spatial data science and how to execute your analysis using a high-performance computer (HPC).
Python
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Python course offered by Texas A&M HPRC
Scipy Lecture Notes
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Comprehensive tutorials and lecture notes covering various aspects of scientific computing using Python and Scipy.
AI powered VsCode Editor
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**Cursor: The AI-Powered Code Editor**
Cursor is a cutting-edge, AI-first code editor designed to revolutionize the way developers write, debug, and understand code. Built upon the premise of pair-programming with artificial intelligence, Cursor harnesses the capabilities of advanced AI models to offer real-time coding assistance, bug detection, and code generation.
**How Cursor Benefits High-Performance Computing (HPC) Work:**
1. **Efficient Code Development:** With AI-assisted code generation, researchers and developers in the HPC realm can quickly write optimized code for simulations, data processing, or modeling tasks, reducing the time to deployment.
2. **Debugging Assistance:** Handling complex datasets and simulations often lead to intricate bugs. Cursor's capability to automatically investigate errors and determine root causes can save crucial time in the HPC workflow.
3. **Tailored Code Suggestions:** Cursor's AI provides context-specific code suggestions by understanding the entire codebase. For HPC applications where performance is paramount, this means receiving recommendations that align with optimization goals.
4. **Improved Code Quality:** With AI-driven bug scanning and linter checks, Cursor ensures that HPC codes are not only fast but also robust and free of common errors.
5. **Easy Integration:** Being a fork of VSCode, Cursor allows seamless migration, ensuring that developers working in HPC can swiftly integrate their existing VSCode setups and extensions.
In essence, for HPC tasks that demand speed, precision, and robustness, Cursor acts as an invaluable co-pilot, guiding developers towards efficient and optimized coding solutions.
It is free if you provide your own OPEN AI API KEY.
AHPCC documentary
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This link is a documentary website to use AHPCC.
GPU Computing Workshop Series for the Earth Science Community
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GPU training series for scientists, software engineers, and students, with emphasis on Earth science applications.
The content of this course is coordinated with the 6 month series of GPU Training sessions starting in Februrary 2022. The NVIDIA High Performance Computing Software Development Kit (NVHPC SDK) and CUDA Toolkit will be the primary software requirements for this training which will be already available on NCAR's HPC clusters as modules you may load. This software is free to download from NVIDIA by navigating to the NVHPC SDK Current Release Downloads page and the CUDA Toolkit downloads page. Any provided code is written specifically to build and run on NCAR's Casper HPC system but may be adapted to other systems or personal machines. Material will be updated as appropriate for the future deployment of NCAR's Derecho cluster and as technology progresses.
How the Little Jupyter Notebook Became a Web App: Managing Increasing Complexity with nbdev
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A tutorial entitled "How the Little Jupyter Notebook Became a Web App: Managing Increasing Complexity with nbdev" presented at SciPy 2023 in Austin, TX. This tutorial is hosted in a series of Jupyter Notebooks which can be accessed in the click of a button using Binder. See the README for more information.
Introductory Python Lecture Series
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A lecture and notes with the goal of teaching introductory python. Starting by understanding how to download and start using python, then expanding to basic syntax for lists, arrays, loops, and methods.
Introduction to Linux CLI for Researchers
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The goal of this video is to help researchers and students recently given allocations to High Performance Compute resources a basic introduction to Linux commands to help them get started. These are a few of the most fundamental commands for navigating and getting started.
If you find this video helpful or would like me to continue this series let me know!
Recommended Libraries for Cyberinfrastructure Users Developing Jupyter Notebooks
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This repository contains information about Jupyter Widgets and how they can be used to develop interactive workflows, data dashboards, and web applications that can be run on HPC systems and science gateways. Easy to build web applications are not only useful for scientists. They can also be used by software engineers and system admins who want to quickly create tools tools for file management and more!
Electric field analyses for molecular simulations
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Tool to compute electric fields from molecular simulations
Conda
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Conda is a popular package management system. This tutorial introduces you to Conda and walks you through managing Python, your environment, and packages.
Building the ArduPilot environment for Linux
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This article provides instructions for building AirSim, an open-source simulator for autonomous vehicles, on Linux. It outlines the steps to build Unreal Engine, clone and build the AirSim repository, and set up the Unreal environment. It also includes information on how to use AirSim and optional setups such as remote control for manual flight.
Applications of Machine Learning in Engineering and Parameter Tuning Tutorial
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Slides for a tutorial on Machine Learning applications in Engineering and parameter tuning given at the RMACC conference 2019.
CI Computing Module For All
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Computing Module: Introduces fundamental concepts and skills of Cyberinfrastructure (CI) and High-Performance Computing (HPC) to lower the barrier to becoming CI users in disaster management research. The module will cover the critical topics of CI and HPC with hands-on sessions.
Disaster Data Module: Introduces concepts of geospatial big data in disaster management. Students will learn how to access and process disaster data.
Geospatial Analytic Module: Introduces geospatial analytics skills to address real-world challenges in disaster management. The module will use the data introduced in the Disaster Data Module and cover various geospatial analytics topics such as geosimulation, spatial optimization, network analysis, terrain analysis, Geospatial Artificial Intelligence (GeoAI), social sensing, and CyberGIS.