- PetIGA, an open-source code for isogeometric analysis0This 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.
- OpenStack Tutorial For Beginners0OpenStack Tutorial For Beginners
- Managing and Optimizing Your Jobs on HPC0An overview of tools and methods to manage and optimize jobs and HPC workflows
- FreeSurfer Tutorials0The official MGH / Harvard tutorial page for FreeSurfer. The FreeSurfer group has provided and designed a series of tutorials for using FreeSurfer and for getting acquainted with the concepts needed to perform its various modes of analysis and processing of MRI data. The tutorials are designed to be followed along in a terminal window where commands can be copy/pasted instead of typed.
- United Nations Mentor Handbook0The 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.
- OpenMP and Multithreaded Jobs in GRASS0Techniques and support for multithreaded geospatial data processing in GRASS.
- Machine Learning with sci-kit learn0In the realm of Python-based machine learning, Scikit-Learn stands out as one of the most powerful and versatile tools available. This introductory post serves as a gateway to understanding Scikit-Learn through explanations of introductory ML concepts along with implementations examples in Python.
- An Introduction to the Julia Programming Language0The 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.
- Horovod: Distributed deep learning training framework0Horovod is a distributed deep learning training framework. Using horovod, a single-GPU training script can be scaled to train across many GPUs in parallel. The library supports popular deep learning framework such as TensorFlow, Keras, PyTorch, and Apache MXNet.
- Advanced Compilers: The Self-Guided Online Course0This is a self guided online course on compilers. The topics covered throughout the course include universal compilers topics like intermediate representations, data flow, and “classic” optimizations as well as more research focusedtopics such as parallelization, just-in-time compilation, and garbage collection.
- Hour of Ci0Hour of Cyberinfrastructure (Hour of CI) is a nationwide campaign to introduce undergraduate and graduate students to cyberinfrastructure and geographic information science (GIS).
- Jetstream Home0Jetstream2 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.
- Open Storage Network0The Open Storage Network, a national resource available through the XSEDE resource allocation system, is high quality, sustainable, distributed storage cloud for the research community.
- ACCESS KB Guide - Expanse0Expanse at SDSC is a cluster designed by Dell and SDSC delivering 5.16 peak petaflops, and offers Composable Systems and Cloud Bursting. This documentation describes how to use the Expanse cluster with some specific information for people with ACCESS accounts.
- Reinforcement Learning For Beginners with Python0This 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!
- Campus Research Computing Consortium (CaRCC)0CaRCC – 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.
- Harnessing the Power of Cloud and Machine Learning for Climate and Ocean Advances0
- Harnessing the Power of Cloud and Machine Learning for Climate and Ocean Advances
- Github for Outputs of Presentation
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 - Wiki for Onboarding onto the C3DDB Cluster at MGHPCC0This 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.
- Introduction to MP0Open Multi-Processing, is an API designed to simplify the integration of parallelism in software development, particularly for applications running on multi-core processors and shared-memory systems. It is an important resource as it goes over what openMP and ways to work with it. It is especially important because it provides a straightforward way to express parallelism in code through pragma directives, making it easier to create parallel regions, parallelize loops, and define critical sections. The key benefit of OpenMP lies in its ease of use, automatic thread management, and portability across various compilers and platforms. For app development, especially in the context of mobile or desktop applications, OpenMP can enhance performance by leveraging the capabilities of modern multi-core processors. By parallelizing computationally intensive tasks, such as image processing, data analysis, or simulations, apps can run faster and more efficiently, providing a smoother user experience and taking full advantage of the available hardware resources. OpenMP's scalability allows apps to adapt to different hardware configurations, making it a valuable tool for developers aiming to optimize their software for a range of devices and platforms.
- How to use Rclone0Learn how to use Rclone to transfer data, specifically from your local drive to the Open Storage Network, vice versa.
- Master’s in Cybersecurity Degree Essentials0Offers comprehensive information on various master's degree options in cybersecurity, including program details, admission requirements, and career opportunities, helping students make informed decisions about pursuing an advanced degree in cybersecurity.
- Introduction to Parallel Computing Tutorial0The 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 .
- High performance computing 1010An introductory guide to High Performance Computing.
Knowledge Base Resources
These resources are contributed by researchers, facilitators, engineers, and HPC admins. Please upvote resources you find useful!