Knowledge Base Resources
Contributed by cyberinfrastructure professionals (researchers, research computing facilitators, research software engineers and HPC system administrators), these resources are shared through the ConnectCI community platform. Add resources you find helpful!
Containerization Explained
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Containerization is a software development method in which applications are packaged into standard units for development, shipment, and deployment.
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.
GPU Acceleration in Python
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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.
PyTorch Introduction
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This is a very barebones introduction to the PyTorch framework used to implement machine learning. This tutorial implements a feed-forward neural network and is taught completely asynchronously through Stanford University. A good start after learning the theory behind feed-forward neural networks.
Using Dask on HPC Systems
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A tutorial on the effective use of Dask on HPC resources. The four-hour tutorial will be split into two sections, with early topics focused on novice Dask users and later topics focused on intermediate usage on HPC and associated best practices. The knowledge areas covered include (but are not limited to):
Beginner section
High-level collections including dask.array and dask.dataframe
Distributed Dask clusters using HPC job schedulers
Earth Science data analysis using Dask with Xarray
Using the Dask dashboard to understand your computation
Intermediate section
Optimizing the number of workers and memory allocation
Choosing appropriate chunk shapes and sizes for Dask collections
Querying resource usage and debugging errors
DELTA Introductory Video
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Introductory video about DELTA. Speaker Tim Boerner, Senior Assistant Director, NCSA
Harnessing the Power of Cloud and Machine Learning for Climate and Ocean Advances
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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
Anvil Documentation
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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.
Awesome Jupyter Widgets (for building interactive scientific workflows or science gateway tools)
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A curated list of awesome Jupyter widget packages and projects for building interactive visualizations for Python code
Trusted CI
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The mission of Trusted CI is to lead in the development of an NSF Cybersecurity Ecosystem with the workforce, knowledge, processes, and cyberinfrastructure that enables trustworthy science and NSF’s vision of a nation that is a global leader in research and innovation.
AI Institutes Cyberinfrastructure Documents: SAIL Meeting
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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.
MATLAB with other Programming Languages
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MATLAB is a really useful tool for data analysis among other computational work. This tutorial takes you through using MATLAB with other programming languages including C, C++, Fortran, Java, and Python.
Molecular Dynamics Tutorials for Beginner's
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Links to MD tutorials for beginner's across various simulation platforms.
Ultimate guide to Unix
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Unix is incredibly common and useful. This website provides all the common commands and explanations for one to get started with a unix system.
TensorFlow for Deep Neural Networks
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TensorFlow is a powerful framework for Deep Learning, developed by google. This specifically is their python package, which is easy to use and can be used to train incredibly powerful models.
Neurostars
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A question and answer forum for neuroscience researchers, infrastructure providers and software developers.
PetIGA, an open-source code for isogeometric analysis
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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.
Samtools Documentation
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Samtools is a suite of programs for interacting with high-throughput sequencing data, especially in the SAM/BAM format. It offers various utilities for processing, analyzing, and managing sequence data generated from next-generation sequencing (NGS) experiments. Samtools is widely used in bioinformatics and genomics research for tasks such as read alignment, variant calling, and data manipulation.
Machine Learning in R online book
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The free online book for the mlr3 machine learning framework for R. Gives a comprehensive overview of the package and ecosystem, suitable from beginners to experts. You'll learn how to build and evaluate machine learning models, build complex machine learning pipelines, tune their performance automatically, and explain how machine learning models arrive at their predictions.
ACCESS Resource Advisor
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A web-based tool to help researchers identify appropriate ACCESS resources for their project.
Charliecloud User Group
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Announcements for for users and developers of Charliecloud, which provides lightweight user-defined software stacks for high-performance computing.
DAGMan for orchestrating complex workflows on HTC resources (High Throughput Computing)
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DAGMan (Directed Acyclic Graph Manager) is a meta-scheduler for HTCondor. It manages dependencies between jobs at a higher level than the HTCondor Scheduler.
It is a workflow management system developed by the High-Throughput Computing (HTC) community, specifically for managing large-scale scientific computations and data analysis tasks. It enables users to define complex workflows as directed acyclic graphs (DAGs). In a DAG, nodes represent individual computational tasks, and the directed edges represent dependencies between the tasks. DAGMan manages the execution of these tasks and ensures that they are executed in the correct order based on their dependencies.
The primary purpose of DAGMan is to simplify the management of large-scale computations that consist of numerous interdependent tasks. By defining the dependencies between tasks in a DAG, users can easily express the order of execution and allow DAGMan to handle the scheduling and coordination of the tasks. This simplifies the development and execution of complex scientific workflows, making it easier to manage and track the progress of computations.
Apache HTTP Server 2.4 Security Vulnerabilities
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The webpage lists known security vulnerabilities affecting Apache HTTP Server 2.4, including detailed descriptions, impact assessments, and mitigation steps. It provides links to official patches, security advisories, and recommendations for keeping servers secure. The page is regularly updated to help administrators stay informed about potential threats and necessary updates.
Campus Champions Home Page
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Campus Champions foster a dynamic environment for a diverse community of research computing and data professionals sharing knowledge and experience in digital research infrastructure.
Installing Rocky Linux Operating System
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Rocky Linux is an open-source enterprise operating system. It is compatible with Red Hat Enterprise Linux (RHEL). It is a community-driven project that provides a stable and reliable platform for production workloads. It is one of the best alternatives to Opensource CentOS, since Centos will be on end of life (EoL) soon in 2024 by shifting to CentOS Stream.