Knowledge Base Resources

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.

In this presentation, I will explore the recent advancements in AI-driven production of 3D-generative assets and environments, particularly focusing on their application in creating immersive, playful experiences. Platforms such as ChatGPT, Suno, and Speechify have ushered in a new era of digital creativity, facilitating the development of environments that not only entertain but also serve educational purposes. This session will delve into how these technologies are integrated into academic settings, specifically through a case study of the English Department's Digital Media Lab, known as Tech/Tech, which opened in 2022.

Documentation and presentation on how to use machine learning and deep learning framework using TensorFlow, Keras and sci-kit learn for Climate and Ocean Advances

Learn Python online with these distance learning courses.

**Termius: The Modern SSH Client for 2023** Termius is the future-facing SSH client that's redefining remote server access in 2023. Designed for ease and efficiency, Termius offers a seamless connection experience across all devices, be it mobile or desktop. Gone are the days of re-inputting IP addresses, ports, and passwords; with Termius, one-click connectivity is the new norm. **How Termius Elevates Remote Server Access:** 1. **One-Click Connectivity:** Save the hassle of remembering and re-entering connection details. Termius provides an immediate connection to your infrastructure with a single click. 2. **Synchronized Across Devices:** Termius ensures that your data, connection settings, and preferences are consistent across all your devices, from mobile to desktop. 3. **Unparalleled Security:** With the Cloud Vault feature, users can securely store their data in an encrypted environment, accessible only from their specific devices. Shared vaults allow for safe connection sharing within teams. 4. **AI-Powered Terminal Experience:** Advanced AI-driven autocomplete means users can input command descriptions, and Termius will swiftly convert them into accurate bash commands, simplifying and enhancing the terminal interaction. 5. **Collaborative Troubleshooting:** Share terminal sessions with teammates, facilitating cooperative problem-solving or knowledge sharing. No additional server-side installations needed. 6. **Automation and Snippets:** Streamline routine processes with the ability to save and run frequently used shell scripts. Sharing these Snippets with your team can lead to increased productivity and fewer manual errors. 7. **All-Device Compatibility:** Whether on iPad, iPhone, Android, macOS, Windows, or Linux, Termius ensures a consistent and fluid experience. The platform's synchronization capability means you're always ready to respond swiftly, irrespective of the device in use. For professionals and businesses aiming for top-notch server access efficiency, Termius is the gold standard in 2023. Experience the revolution in SSH connectivity and optimize your workflow with Termius.

The Open Storage Network, a national resource available through the XSEDE resource allocation system, is high quality, sustainable, distributed storage cloud for the research community.

It's not uncommon to see beautiful visualizations in HPC center galleries, but the majority of these are either rendered off the HPC or created using programs that run on OpenGL or custom rasterization techniques. To put it simply the next generation of graphics provided by OpenGL's successor Vulkan is strangely absent in the super computing world. The aim of this survey of available resources is to determine the systems that can support Vulkan workflows and programs. This will assist users in getting past some of the first hurdles in using Vulkan in HPC contexts.

This package lets you easily scrape websites and extract information based on html tags and various other metadata found in the page. It can be useful for large-scale web analysis and other tasks requiring automated data gathering.

This course takes through the fundamentals required to get started with reinforcement learning with Python, OpenAI Gym and Stable Baselines. You'll be able to build deep learning powered agents to solve a varying number of RL problems including CartPole, Breakout and CarRacing as well as learning how to build your very own/custom environment!

R for Data Science is a comprehensive resource for individuals looking to harness the power of the R programming language for data analysis, visualization, and statistical modeling. Whether you're a beginner or an experienced data scientist, this guide will help you unlock the full potential of R in the realm of data science.

This tutorial is essentially the "hello world" of image recognition and feed-forward neural network (using PyTorch). Using the MNIST database (filled within images of handwritten digits), the tutorial will instruct how to build a feed-forward neural network that can recognize handwritten digits. A solid understanding of feed-forward and back-propagation is recommended.

A question and answer forum for neuroscience researchers, infrastructure providers and software developers.

The CyberAmbassadors project was funded through a workforce development grant from the National Science Foundation (Award #1730137). Starting in 2017, the initial focus of this project was to develop, test, and refine new curriculum to help CyberInfrastructure (CI) Professionals strengthen their communications, teamwork and leadership skills. With support and collaboration from a number of academic and professional organizations, the CyberAmbassadors project was expanded to offer professional skills training to college students and professionals working across STEM (science, technology, engineering, math) disciplines.

The provided text discusses various aspects of Android app development fundamentals. It covers key concepts related to app components, the AndroidManifest.xml file, and app resources. Android apps are built using various components, including Activities, Services, Broadcast Receivers, and Content Providers. These components serve different purposes and have distinct lifecycles. Activities are used for user interaction, services for background tasks, broadcast receivers for system-wide event handling, and content providers for managing shared data.The AndroidManifest.xml file is essential for declaring app components, permissions, and other settings. It informs the Android system about the app's components and capabilities. For instance, it specifies the minimum API level, declares hardware and software requirements, and defines intent filters to enable components to respond to specific actions.It's crucial to declare app requirements, such as device features and minimum Android API levels, to ensure compatibility with different devices and configurations. These declarations help in filtering the app's availability on Google Play for users with compatible devices.Android apps rely on resources separate from code, including images, layouts, strings, and more. These resources are stored in various directories and can be tailored for different device configurations. Providing alternative resources allows for optimization across different languages, screen sizes, orientations, and other factors. Understanding these fundamentals is essential for developing Android applications effectively, ensuring compatibility, and providing a consistent user experience across a wide range of devices and configurations.

Learn how to use Rclone to transfer data, specifically from your local drive to the Open Storage Network, vice versa.

A VPN, or Virtual Private Network, is a technology that creates a secure tunnel between your device and a VPN server. This tunnel encrypts all of your traffic, making it unreadable to anyone who tries to intercept it.

The tutorial is intended to provide a brief overview of the extensive and broad topic of Parallel Computing. It covers the basics of parallel computing, and is intended for someone who is just becoming acquainted with the subject .

This website is an interactive introduction to Gaussian Belief Propagation (GBP). A probabilistic inference algorithm that operates by passing messages between the nodes of arbitrarily structured factor graphs. A special case of loopy belief propagation, GBP updates rely only on local information and will converge independently of the message schedule. The key argument is that, given recent trends in computing hardware, GBP has the right computational properties to act as a scalable distributed probabilistic inference framework for future machine learning systems.

Data augmentation is a crucial step in the pipeline for image classification with deep learning. Albumentations is an extremely versatile Python library that can be used to easily augment images. Transformations include rotations, flips, downscaling, distortions, blurs, and many more. Citation: Buslaev A, Iglovikov VI, Khvedchenya E, Parinov A, Druzhinin M, Kalinin AA. Albumentations: Fast and Flexible Image Augmentations. Information. 2020; 11(2):125. https://doi.org/10.3390/info11020125

pip stands for "pip installs packages". It's the go-to package manager for Python, allowing developers to install, update, and manage software libraries and dependencies used in Python projects. With just a few commands in your terminal or command prompt, pip makes it effortless to fetch libraries from the Python Package Index (PyPI) and integrate them into your projects. This guide will walk you through the basics of pip, from installation to advanced package management.

In this tutorial, I present an overview with many examples of the use of Numpy and Pandas for data analysis. Beginners in the field of data analysis can find It incredibly helpful, and at the same time, anyone who already has experience in data analysis and needs a refresher can find value in it. I discuss the use of Numpy for analyzing 1D and 2D multidimensional data and an introduction on using Pandas to manipulate CSV files.

Plots.jl is the most widely used plotting library for the Julia programming language. It's known for being especially powerful in its versatility and intuitiveness. It's limited set of dependencies and wide applicability across different graphics packages make it especially helpful in visualizing the results of your latest Julia implementation. However, there are still multiple options available for Julia programmers to visualize their datasets. The second link details a comparison against a variety of Julia packages.

A series of interviews with women in the HPC community