• https://mc-stan.org/users/documentation/
• https://vasishth.github.io/bayescogsci/book/ch-introstan.html
• https://pystan.readthedocs.io/en/latest/

The Stan language is used to specify a (Bayesian) statistical model with an imperative program calculating the log probability density function. Here are some useful links to start your exploration of this statistical programming language, and a Python interface to Stan.

• Framework to help in scaling Machine Learning/Deep Learning/AI/NLP Models to Web Application level

This framework will help in scaling Machine Learning/Deep Learning/Artificial Intelligence/Natural Language Processing Models to Web Application level almost without any time.

• Cursor - AI code editor

**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.

• Trinity Tutorial for Transcriptome Assembly

Trinity is one of the most popular tool to assemble transcripts from RNA-Seq short reads. In this tutorial, we will cover the basic usage of Trinity, best practice and common problems.

• C Programming Notes

"These notes are part of the UW Experimental College course on Introductory C Programming. They are based on notes prepared (beginning in Spring, 1995) to supplement the book The C Programming Language, by Brian Kernighan and Dennis Ritchie, or K&R as the book and its authors are affectionately known. (The second edition was published in 1988 by Prentice-Hall, ISBN 0-13-110362-8.) These notes are now (as of Winter, 1995-6) intended to be stand-alone, although the sections are still cross-referenced to those of K&R, for the reader who wants to pursue a more in-depth exposition." C is a low-level programming language that provides a deep understanding of how a computer's memory and hardware work. This knowledge can be valuable when optimizing apps for performance or when dealing with resource-constrained environments.C is often used as the foundation for creating cross-platform libraries and frameworks. Learning C can allow you to develop libraries that can be used across different platforms, including iOS, Android, and desktop environments.

• Github Wiki

This is a resource for researchers and students looking to on-board onto the c3ddb cluster at MGHPCC. In the code section, there are example job submission scripts for the different queues on c3ddb.

• Chameleon User Guide

Chameleon is an NSF-funded testbed system for Computer Science experimentation. It is designed to be deeply reconfigurable, with a wide variety of capabilities for researching systems, networking, distributed and cluster computing and security.

• AWS Tutorial For Beginners

An AWS Tutorial for Beginners is a course that teaches the basics of Amazon Web Services (AWS), a cloud computing platform that offers a wide range of services, including compute, storage, networking, databases, analytics, machine learning, and artificial intelligence.

• OpenMP and Multithreaded jobs in GRASS

Techniques and support for multithreaded geospatial data processing in GRASS.

• Spatial Data Science in the Cloud (Alpine HPC) using Python Webpage

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).

• Official PyTorch Documentation
• Official NumPy Documentation

The official documentation for PyTorch, a machine learning tensor-based framework, and NumPy, which allows for support for ndarrays which is useful to make tensors when implementing NNs. Both libraries can be installed with pip.

• Vulkan Support Survey across Systems
• OSF article link (easier to read)

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.

• pandas documentation

Pandas is one of the most essential Python libraries for data analysis and manipulation. It provides high-performance, easy-to-use data structures, and data analysis tools for the Python programming language. The official documentation serves as an in-depth guide to using this powerful tool including explanations and examples.

• AI-Generated Text Detection In 2023

Documentation and research based on the latest NLP text generation detection methods for 2023.

• Learn Regular Expressions with simple, interactive exercises
• An online tool to learn, build, & test Regular Expressions
• An Online tool that lets you enter your own text and regular expressions to see what matches

Regular expressions (sometimes referred to as RegEx) is an incredibly powerful tool that is used to define string patterns for "find" or "find and replace" operations on strings, or for input validation. Regular Expressions are used in search engines, in search and replace dialogs of word processors and text editors, and text-processing Linux utilities such as sed and awk. They are supported in many programming languages, including Python, R, Perl, Java, and others.

• Texas A&M Research Computing Training Resources

Training Resources and Courses offered by Texas A&M's Research Computing Group

• Long Tales of Science

A series of interviews with women in the HPC community

• Regulated Research Community of Practice

The daily news clearly shows the increasing threat to safety and privacy of data, personal as well as intellectual property. While the requirements such as DFARS 7012, HIPAA, and Cybersecurity Maturity Model Certification (CMMC) improve the consistency of data handling between agencies and contractors and grantees, it leaves academic institutions to figure out how to meet such requirements in a cost-effective way that fits the research and education mission of the institution. Most institutions, agencies, and companies act in isolation with one-off contract language to address data security and safeguarding concerns. Even though cybersecurity has a clear and uniform goal of protecting data, a onesize solution does not fit all academic institutions. By supporting this community with development of a community strategic roadmap, regular discussions and workshops, and a repository of generalized and specific resources for handling regulated research programs RRCoP lowers the barrier to entry for institutions handling new regulations.

• fast.ai Homepage

Fastai offers many tools to people working with machine learning and artifical intelligence including tutorials on PyTorch in addition to their own library built on PyTorch, news articles, and other resources to dive into this realm.

• Reinforcement Learning For Beginners with Python

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!

• Docs

MediaPipe is Google's open-source framework for building multimodal (e.g., video, audio, etc.) machine learning pipelines. It is highly efficient and versatile, making it perfect for tasks like gesture recognition. This is a tutorial on how to make a custom model for gesture recognition tasks based on the Google MediaPipe API. This tutorial is specifically for video-playback, though could be generalized to image and live-video feed recognition.

• RMACC Sys Admin Workshop '24 Slides

A compilation of the slides from this year's RMACC Sys Admin Workshop. RMACC Sys Admin Workhop Schedule: Tuesday 12:00 PM Sign-in 1:00 PM Introductions 1:30 PM Lightning Talk - HPC Survival guide 2:00 PM Node Management - Scott Serr 2:30 PM Lightning Talk - Warewulf 3:00 PM Urgent HPC - Coltran Hophan-Nichols and Alexander Salois Wednesday 9:00 AM Breakfast 10:00 AM Round table Sites - BYU, INL, UMT, ASU, MSU 11:00 AM Open OnDemand setup - Dean Anderson 11:30 AM Lightning talk - Long term hardware support 12:00 PM Lunch 1:00 PM HPC Security - Matt Bidwell 2:00 PM Lightning talk- Security 2:30 PM ACCESS resources - Couso 3:00 PM Easybuild tutorial - Alexander Salois 3:30 PM General Q & A Thursday 9:00 AM Breakfast 10:00 AM Lightning Talk- Containers and Virtual Machines 11:00 AM University of Montana - Hellgate Site Tour 11:30 AM Closing Remarks

• NumPY Docs

Numpy is a python package that leverages types and compiled C code to make many math operations in Python efficient. It is especially useful for matrix manipulation and operations.

• Neurodesk

Neurodesk provides a containerised data analysis environment to facilitate reproducible analysis of neuroimaging data. Analysis pipelines for neuroimaging data typically rely on specific versions of packages and software, and are dependent on their native operating system. These dependencies mean that a working analysis pipeline may fail or produce different results on a new computer, or even on the same computer after a software update. Neurodesk provides a platform in which anyone, anywhere, using any computer can reproduce your original research findings given the original data and analysis code.

• https://www.mathworks.com/products/bioinfo.html

Bioinformatics Toolbox provides algorithms and apps for Next Generation Sequencing (NGS), microarray analysis, mass spectrometry, and gene ontology. Using toolbox functions, you can read genomic and proteomic data from standard file formats such as SAM, FASTA, CEL, and CDF, as well as from online databases such as the NCBI Gene Expression Omnibus and GenBank.