OpenMP and Multithreaded Jobs in GRASS
0
Techniques and support for multithreaded geospatial data processing in GRASS.
Beautiful Soup - Simple Python Web Scraping
0
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.
MNIST Handwritten Digits Tutorial
0
This tutorial will give you an introduction to neural networks using the ever-famous MNIST handwritten digits database!
Presented by Robin Hwang.
Vulkan Support Survey across Systems
0
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.
R for Data Science
0
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.
Handwritten Digits Tutorial in PyTorch
0
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.
An Introduction to the Julia Programming Language
0
The Julia Programming Language is one of the fastest growing software languages for AI/ML development. It writes in manner that's similar to Python while being nearly as fast as C++, while being open source, and reproducible across platforms and environments. The following link provide an introduction to using Julia including the basic syntax, data structures, key functions, and a few key packages.
Application Fundamentals (Android)
0
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.
Regulated Research Community of Practice
0
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.
Natural Language Processing with Deep Learning
0
CS244N is a renowned natural language processing course offered by Stanford University and taught by Christopher Manning. It covers a wide range of topics in NLP, including language modeling, machine translation, sentiment analysis, and more. It teaches both foundational concepts and cutting-edge research to gain a comprehensive understanding of NLP techniques and applications.
Reinforcement Learning For Beginners with Python
0
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!
What is VPN? How It Works, Types of VPN
0
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.
Expanse Home Page
0
Expanse at SDSC is a cluster designed by Dell and SDSC delivering 5.16 peak petaflops, and offers Composable Systems and Cloud Bursting.
Language models and using HPC resources
0
Documentation and research based on the latest NLP text generation detection methods for 2023.
Intro to GenAI Chatbot
0
Neurodesk
0
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.
A guide to pip in Python
0
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.
Campus Research Computing Consortium (CaRCC)
0
CaRCC – the Campus Research Computing Consortium – is an organization of dedicated professionals developing, advocating for, and advancing campus research computing and data and associated professions.
Vision: CaRCC advances the frontiers of research by improving the effectiveness of research computing and data (RCD) professionals, including their career development and visibility, and their ability to deliver services and resources for researchers. CaRCC connects RCD professionals and organizations around common objectives to increase knowledge sharing and enable continuous innovation in research computing and data capabilities.
Automated Machine Learning Book
0
The authoritative book on automated machine learning, which allows practitioners without ML expertise to develop and deploy state-of-the-art machine learning approaches. Describes the background of techniques used in detail, along with tools that are available for free.
R for Research Scientists
0
A book for researchers who contribute code to R projects: This booklet is the result of my work with the Social Cognition for Social Justice lab. It was developed in response to questions I was getting from students; both grad students that were making software design decisions, and undergraduates who were using things like version control for the first time. Although many tutorials and resources exist for these topics, there was not a single source that I thought covered just enough material to build up to the workflow used by the lab without extraneous detail.
Introduction to Parallel Computing Tutorial
0
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 .
CMake Tutorials
0
CMake is an open-source tool used to manage the build process in operating systems. This tutorial takes you through how to use CMake from the very basics with example projects.
EasyBuild Documentation
0
EasyBuild is a software installation framework that allows administrators to easily build and install software on high-performance computing (HPC) systems. It supports a wide range of software packages, toolchains, and compilers.
Supported software are found in the EasyConfigs repository, one of several resositories in EasyBuild project.
Slurm Scheduling Software Documentation
0
Slurm is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. Slurm requires no kernel modifications for its operation and is relatively self-contained. As a cluster workload manager, Slurm has three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allocated nodes. Finally, it arbitrates contention for resources by managing a queue of pending work.
Learn Python Online
0
Learn Python online with these distance learning courses.