• WarpX website

WarpX is an advanced particle-in-cell code used to model particle accelerators, which needs to be run on HPC. This website contains the tutorial on how to build WarpX on various HPC systems such as NERSC along with examples on how to set up post-processing/visualization tools for different physics cases.

• Data Analysis with R for Educators

This webinar series is an orientation to R. We start with an overview of R’s history and place in the larger data science ecosystem. Next, we introduce the R Studio user interface and how to access R’s excellent documentation. Finally, we present the fundamental concepts you need to use the R environment and language for data analysis. Along the way, we compare R script files (.R) to R Notebook (.Rmd) files and show how the features of R Notebook support better communication and encourage more dynamic engagement with statistical analysis and code. It is helpful to be familiar with tabular data analysis using statistical software, database tools, or spreadsheet programs. Workshop materials, including setup directions and slides are available at https://github.com/CornellCAC/r_for_edu/ The Rstudio Cloud project used in the workshop is https://rstudio.cloud/project/4044219.

• JupyterLabIDE GitHub Repository

Iterative Programming takes place when you can explore your code and play with your objects and functions without needing to save, recompile, or leave your development environment. This has traditionally been achieved with a REPL or an interactive shell. The magic of Jupyter Notebooks is that the interactive shell is saved as a persistant document, so you don't have to flip back and forth between your code files and the shell in order to program iteratively. There are several editors and IDE's that are intended for notebook development, but JupyterLab is a natural choice because it is free and open source and most closely related to the Jupyter Notebooks/iPython projects. The chief motivation of this repository is to enable an IDE-like development environment through the use of extensions. There are also expositional notebooks to show off the usefulness of these features.

• DeepChem Tutorial

DeepChem is an open-source library built on TensorFlow and PyTorch. It is helpful in applying machine learning algorithms to molecular data.

• CaRCC Data Facing Track Page

The Data-Facing Track of the People Network brings together people from research computing groups, libraries, research institutes, and other organizations who support data-enabled research. Many of us are also Researcher-Facing, but this track is an opportunity to discuss the varied challenges of working with data.

• The right mentor can change your career. Here's how to find one.

Pluses and challenges of mentor selection. Offers tips for acquiring a mentor (finding, asking). And how to be a good mentee. SMART framework mentioned. Discrimination mentioned. Difference between mentor and sponsor underlined. More than one mentor encouraged. Good tips.

• Tutorial - Using Rclone to transfer data into the OSN

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

• DELTA Youtube Video

Introductory video about DELTA. Speaker Tim Boerner, Senior Assistant Director, NCSA

• Fairness and Machine Learning

The "Fairness and Machine Learning" book offers a rigorous exploration of fairness in ML and is suitable for researchers, practitioners, and anyone interested in understanding the complexities and implications of fairness in machine learning.

• Onshape Onboarding

This contains documentation for getting started with using OnShape for CAD. OnShape cloud-hosted CAD software that lets you work with others like on a Google Doc, with the power and capabilities of any other software like Solidworks or Inventor.

• GPU Acceleration in Python

This tutorial explains how to use Python for GPU acceleration with libraries like CuPy, PyOpenCL, and PyCUDA. It shows how these libraries can speed up tasks like array operations and matrix multiplication by using the GPU. Examples include replacing NumPy with CuPy for large datasets and using PyOpenCL or PyCUDA for more control with custom GPU kernels. It focuses on practical steps to integrate GPU acceleration into Python programs.

• https://snakemake.readthedocs.io/en/stable/

Snakemake is a powerful and versatile workflow management system that simplifies the creation, execution, and management of data analysis pipelines. It uses a user-friendly, Python-based language to define workflows, making it particularly valuable for automating and reproducibly managing complex computational tasks in research and data analysis.

• Singularity Documentation
• Apptainer Documentation

Singularity/Apptainer is a free and open-source container platform that allows users to build and run containers on high performance computing resources. SingularityCE is the community edition of Singularity maintained by Sylabs, a company that also offers commercial Singularity products and services. Apptainer is a fork of Singularity, maintained by the Linux foundation, a community of developers and users who are passionate about open source software.

• Termius

**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.

• Slurm Community Mailing List

• Anvil Documentation

Documentation for Anvil, a powerful supercomputer at Purdue University that provides advanced computing capabilities to support a wide range of computational and data-intensive research spanning from traditional high-performance computing to modern artificial intelligence applications.

• How do you add your institutional HPC cluster to the Open Science Grid (OSG)?

Discussion about contributing cycles to the Open Science Grid.

• Beautiful Soup Docs

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.

• Ask.CI

• Recording of CI ACCESS Talk
• Flyer about ACCESS
• Slides from CI ACCESS Talk

Materials from the SAIL meeting (https://aiinstitutes.org/2023/06/21/sail-2023-summit-for-ai-leadership/). A space where AI researchers can learn about using ACCESS resources for AI applications and research.

• University of Arizona Visualization homepage
• Getting Started with Paraview
• Paraview Cameras and Keyframes
• Graphs and Data Exporting
• Visualizing netcdf files

These links take you to visualization resources supported by the University of Arizona's HPC visualization consultant (rtdatavis.github.io). The following links are specific to the Paraview program and the workflows that have been used my researchers at the U of Arizona. Some of the pages linked are very beginner friendly: getting started, working with cameras and keyframes for rendering, visualizing external files (netcdf climate data), graphs and data exporting. Many of the workflows involve using remote desktops via the Open On Demand interface, but if this isn't set up at your university you can use paraview locally on a desktop. Feel free to post on access ci https://ask.cyberinfrastructure.org/ if you need assistance getting a paraview gui open for your work on HPC.

• https://r4ds.had.co.nz/index.html

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.

• Application Fundamentals

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.

• Probabilistic Semantic Data Association for Collaborative Human-Robot Sensing

Humans cannot always be treated as oracles for collaborative sensing. Robots thus need to maintain beliefs over unknown world states when receiving semantic data from humans, as well as account for possible discrepancies between human-provided data and these beliefs. To this end, this paper introduces the problem of semantic data association (SDA) in relation to conventional data association problems for sensor fusion. It then, develops a novel probabilistic semantic data association (PSDA) algorithm to rigorously address SDA in general settings. Simulations of a multi-object search task show that PSDA enables robust collaborative state estimation under a wide range of conditions.

• github link
• documentation link

This documentation provides an overview of the PetIGA framework, an open source code for solving multiphysics problems with isogeometric analysis. The documentation covers some simple tutorials and examples to help users get started with the framework and apply it to solve real-world problems in continuum mechanics, including solid and fluid mechanics.