Bioinformatics Workflow Management with Nextflow
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Nextflow is an open-source, domain-specific language and workflow manager designed for the execution and coordination of scientific and data-intensive computational workflows. It was specifically created to address the challenges faced by researchers and scientists when dealing with complex and scalable computational pipelines, particularly in fields such as bioinformatics, genomics, and data analysis.
Here provided some links to start with.
Neural Networks in Julia
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Making a neural network has never been easier! The following link directs users to the Flux.jl package, the easiest way of programming a neural network using the Julia programming language. Julia is the fastest growing software language for AI/ML and this package provides a faster alternative to Python's TensorFlow and PyTorch with a 100% Julia native programming and GPU support.
AHPCC documentary
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This link is a documentary website to use AHPCC.
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.
Displaying Scientific Data with Tableau
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Tableau is a popular and capable software product for creating charts that present data and dashboards that allow you to explore data. It is typically used to present business or statistical data, but can also create compelling visualizations of scientific data. However, scientific data is often generated or stored in formats that are not immediately accessible by Tableau. This seminar will explore the data formats that work best with Tableau and the available mechanisms for generating scientific data in (or converting it to) those formats so that you can apply the full power of Tableau to create the best possible visualizations of your data.
MPI Resources
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Workshop for beginners and intermediate students in MPI which includes helpful exercises. Open MPI documentation.
Time-Series LSTMs Python Walkthrough
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A walkthrough (with a Google Colab link) on how to implement your own LSTM to observe time-dependent behavior.
Jetstream2 Docs Site
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Jetstream2 makes cutting-edge high-performance computing and software easy to use for your research regardless of your project’s scale—even if you have limited experience with supercomputing systems.Cloud-based and on-demand, the 24/7 system includes discipline-specific apps. You can even create virtual machines that look and feel like your lab workstation or home machine, with thousands of times the computing power.
Vulkan Support Survey across Systems
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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.
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.
ACCESS KB Guide - DELTA
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NCSA is the home of Delta, a computing and data resource that balances cutting-edge graphics processor and CPU architectures with a non-POSIX file system with a POSIX-like interface. Delta allows applications to reap the benefits of modern file systems without rewriting code.
Natural Language Processing with Deep Learning
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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.
ACCESS Guide (originally given at Duke OIT)
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A guide for Duke OIT on how to advise users on using ACCESS and allocation credits to jetstream 2 for Duke University members. This can be used for non Duke members. Assumes the reader has basic knowledge of ACCESS.
Neurostars
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A question and answer forum for neuroscience researchers, infrastructure providers and software developers.
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.
Regulated Research Community of Practice
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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.
Numpy - a Python Library
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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.
Bash shell tutorial
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Training materials for using the bash (and zsh) shell.
Anvil Home Page
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Purdue University is the home of Anvil, a powerful supercomputer 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.
OpenMP Tutorial
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OpenMP (Open Multi-Processing) is an API that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows. It consists of a set of compiler directives, library routines, and environment variables that influence run-time behavior.
Application Fundamentals (Android)
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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.
OpenMP and Multithreaded Jobs in GRASS
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Techniques and support for multithreaded geospatial data processing in GRASS.
Weka
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Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization.
Vulkan Support Survey across Systems
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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.
CyberAmbassadors: Professional Skills for Interdisciplinary Work
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The CyberAmbassadors project was funded through a workforce development grant from the National Science Foundation (Award #1730137). Starting in 2017, the initial focus of this project was to develop, test, and refine new curriculum to help CyberInfrastructure (CI) Professionals strengthen their communications, teamwork and leadership skills. With support and collaboration from a number of academic and professional organizations, the CyberAmbassadors project was expanded to offer professional skills training to college students and professionals working across STEM (science, technology, engineering, math) disciplines.