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!
GPU Acceleration in Python
0
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.
Representation Learning in Deep Learning
0
Representation learning is a fundamental concept in machine learning and artificial intelligence, particularly in the field of deep learning. At its core, representation learning involves the process of transforming raw data into a form that is more suitable for a specific task or learning objective. This transformation aims to extract meaningful and informative features or representations from the data, which can then be used for various tasks like classification, clustering, regression, and more.
Awesome Jupyter Widgets (for building interactive scientific workflows or science gateway tools)
0
A curated list of awesome Jupyter widget packages and projects for building interactive visualizations for Python code
Trusted CI
0
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.
MATLAB with other Programming Languages
0
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
0
Links to MD tutorials for beginner's across various simulation platforms.
Anvil Documentation
0
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.
Ultimate guide to Unix
0
Unix is incredibly common and useful. This website provides all the common commands and explanations for one to get started with a unix system.
Harnessing the Power of Cloud and Machine Learning for Climate and Ocean Advances
0
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
AI Institutes Cyberinfrastructure Documents: SAIL Meeting
0
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.
ACCESS Resource Advisor
0
A web-based tool to help researchers identify appropriate ACCESS resources for their project.
Samtools Documentation
0
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
0
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.
Charliecloud User Group
0
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)
0
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.
PetIGA, an open-source code for isogeometric analysis
0
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.
TensorFlow for Deep Neural Networks
0
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
0
A question and answer forum for neuroscience researchers, infrastructure providers and software developers.
Installing Rocky Linux Operating System
0
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.
United Nations Mentor Handbook
0
The United Nations (UN) is an international organization comprising 193 Member States, including the United States. As a global organization, the UN is the one place on Earth where the world's nations can gather to discuss common problems and find shared solutions that benefit all humanity. This handbook has been produced for UN staff of all backgrounds and levels and provides an overview of how to approach your participation in a mentorship program. This resource is quickly digestible and provides a basic structure that will be helpful to review before the first meeting with your mentee.
Oakridge Leadership Computing Facility (OLCF) Training Events and Archive
0
Upcoming training events and archives of training materials detailing general HPC best practices as well as how to use OLCF resources and services.
Data Imputation Methods for Climate Data and Mortality Data
0
This slices and videos introduced how to use K-Nearest-Neighbors method to impute climate data and how to use Bayesian Spatio-Temporal models in R-INLA to impute mortality data. The demos will be added soon.
Discover Data Science
0
Discover Data Science is all about making connections between prospective students and educational opportunities in an exciting new, hot, and growing field – data science.
Introduction to Parallel Programming for GPUs with CUDA
0
This tutorial provides a comprehensive introduction to CUDA programming, focusing on essential concepts such as CUDA thread hierarchy, data parallel programming, host-device heterogeneous programming model, CUDA kernel syntax, GPU memory hierarchy, and memory optimization techniques like global memory coalescing and shared memory bank conflicts. Aimed at researchers, students, and practitioners, the tutorial equips participants with the skills needed to leverage GPU acceleration for scalable computation, particularly in the context of AI.
Numba: Compiler for Python
0
Numba is a Python compiler designed for accelerating numerical and array operations, enabling users to enhance their application's performance by writing high-performance functions in Python itself. It utilizes LLVM to transform pure Python code into optimized machine code, achieving speeds comparable to languages like C, C++, and Fortran. Noteworthy features include dynamic code generation during import or runtime, support for both CPU and GPU hardware, and seamless integration with the Python scientific software ecosystem, particularly Numpy.