/tag/hpc

  • Rivanna

    Rivanna is the University of Virginia’s High-Performance Computing (HPC) system. As a centralized resource it has hundreds of pre-installed software packages available for computational research across many disciplines. Currently the Rivanna supercomputer has 603 nodes with over 20476 cores and 8PB of various storage.
    All UVA faculty, staff, and postdoctoral associates are eligible to use Rivanna, or students when part of faculty research.
    Facilities Statement - Are you submitting a grant proposal and need standard information about UVA research computing environments? Get it here. The sections below contain important information for new and existing Rivanna users. Please read each carefully.

  • Anaconda on Rivanna

    Overview Built to complement the rich, open source Python community, the Anaconda platform provides an
    enterprise-ready data analytics platform that empowers companies to adopt a modern open data science
    analytics architecture.
    Rivanna has Python 2 and 3 available as part of the Anaconda
    distribution. Anaconda comes installed with many packages best suited
    for scientific computing, data processing, and data analysis, while making deployment
    very simple. Its package manager conda installs and updates python packages and
    dependencies, keeping different package versions isolated on a project-by-project basis.
    Anaconda is available as open source under the New BSD license. It also ships
    with pip, the common python package manager.

  • RC's Data Analytics Center (DAC): Now Serving UVA's Research Community

    The Data Analytics Center is UVA’s new hub for the management and analysis of your large research data. Need help with your computational research? DAC staff specialize in key domain areas such as image processing, text analysis, bioinformatics, computational chemistry and physics, neural networks, and more. And because the DAC team is located within Research Computing, they can assist in getting your workflows running on the University’s high-performance cluster or secure data system. They can answer your basic computational questions or, through funded engagements, be embedded in your projects.
    Big data doesn’t have to be a big deal. Learn how DAC can assist with your computational research – schedule an initial consultation with one of their data analysts by submitting a consultation request.

  • Allocations

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  • Virginia Women in HPC Events in September & October

    VA-WHPC September Event - Leadership Journeys Time: Sep 19, 2023, 01:00 PM EST (US and Canada).
    Join us for our next community event featuring Dr. Neena Imam as she shares her personal view of challenges and successes experienced throughout her inspiring leadership journey in research, HPC and AI computing. Come learn about career strategies, ask questions, and contribute to our discussion of how the playing field may be leveled to offer equitable IT & HPC leadership opportunities for women and minorities.
    Dr. Imam earned a PhD in Electrical Engineering and has been engaged in research and computing in a variety of roles.

  • NVIDIA DGX BasePOD™

    Introducing the NVIDIA DGX BasePOD™ As artificial intelligence (AI) and machine learning (ML) continue to change how academic research is conducted, the NVIDIA DGX BasePOD, or BasePOD, brings new AI and ML functionality to Rivanna, UVA’s High-Performance Computing (HPC) system. The BasePOD is a cluster of high-performance GPUs that allows large deep-learning models to be created and utilized at UVA.
    The NVIDIA DGX BasePOD™ on Rivanna, hereafter referred to as the POD, is comprised of:
    10 DGX A100 nodes with 2TB of RAM memory per node 80 GB GPU memory per GPU device Compared to the regular GPU nodes, the POD contains advanced features such as:

  • GPU-enabled Software on Rivanna

    Please note that certain modules can only run on specific GPU types. This will be displayed in a message upon loading the module.
    Certain software applications may also able to take advantage of the advanced capabilities provided by the NVIDIA DGX BasePOD™.
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  • Virginia Women in HPC - Student Lightning Talks

    What: Join us in welcoming 11 undergraduate and graduate students from across Virginia to talk about their research. The talks will be lightning style format allowing 3 minutes for students to present and 1-2 questions and 1-2 questions from the audience. Don’t miss out on this fantastic opportunity to hear about a variety of research topics within HPC!
    Event Time: April 4, 2023, 01:00 PM EST (US and Canada).
    Register now   Featured Speakers: Lakshmi Miller - Graduate Student
    Aerospace and Ocean Engineering, Virginia Tech
    “CFD Informed Maneuvering of AUVs”
    Rashmi Chawla - Graduate Student
    Aerospace Engineering, Virginia Tech

  • Workshops

    UVA Research Computing provides training opportunities covering a variety of data analysis, basic programming and computational topics. All of the classes listed below are taught by experts and are freely available to UVa faculty, staff and students.
    Upcoming Workshops DATE WORKSHOP INSTRUCTOR There are currently no training events scheduled. Please check back soon! Research Computing is partnering with the Research Library and the Health Sciences Library to deliver workshops covering a variety of
    research computing topics.
    All Upcoming Workshops from UVA Library Research Data Services
    All Upcoming Workshops from UVA Health Sciences Library

  • Virginia Women in HPC - Women in HPC & IT Leadership Roles

    Topic: Women in HPC & IT Leadership Roles.
    When: October 12, 2022 01:00 PM, Eastern Time (US and Canada).
    Join us for our Fall community meeting to hear from female leaders in the HPC & IT field sharing challenges and successes experienced throughout their careers. Don’t miss this fantastic opportunity to learn about career strategies, share your experience, and contribute to our discussion of how the playing field may be leveled to offer equitable HPC & IT leadership opportunities for women and minorities. Attendees are invited to share their own experiences and engage with panelists during this interactive Q&A session.

  • `ssh` on Rivanna

    The secure shell ssh is the primary application used to access Rivanna from the command line.
    Connecting to a Remote Host For Windows, MobaXterm is our recommended ssh client; this package also provides an SFTP client and an X11 server in one bundle.
    Mac OSX and Linux users access the cluster from a terminal through OpenSSH, which are preinstalled on these operating systems. Open a terminal (on OSX, the Terminal application) and type
    ssh -Y mst3k@rivanna.hpc.virginia.edu where mst3k should be replaced by your user ID. You will generally need to use this format unless you set up your user account on your Mac or Linux system with your UVA ID.

  • Mission

    Research Computing empowers UVA researchers to achieve more with cutting-edge computational resources. Our support team strives to create innovative solutions for researchers who need help solving complex optimization, parallelization, workflow, and data analysis issues. We build and maintain the University’s best computing platforms while educating the next generation of researchers on the power of advanced computing.
  • Rivanna Storage

    There are a variety of options for storing large-scale research data at UVa. Public and Internal Use data storage systems can be accessed from the Rivanna high performance computing system.
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  • Service Map

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  • The Make Tool

    Overview Make is a program used primarily on Unix systems to manage compiling and linking (building) programs written in C, C++, Fortran, or other compiled languages. Make operates on targets using rules to create those targets. It has a set of built-in rules but users may write their own or override the default rules. Make scans the dependencies of each target looking for files newer than the target. If it finds them, it recreates the target. Targets may and usually do depend on other targets; make will work its way through the chain to rebuild the final target, which is typically an executable.
  • BART Web

    BART (Binding Analysis for Regulation of Transcription) Web Working with researchers in the Zang Lab in the Center for Public Health Genomics
    (CPHG), RC helped launch BARTweb,
    an interactive web-based tool for users to analyze their Genelist or ChIP-seq datasets. BARTweb is a containerized
    Flask front-end (written in Python) that ingests files and submits them to a more robust Python-based genomics pipeline
    running on Rivanna, UVA’s high performance computing cluster (HPC). This architecture – of a public web application that
    uses a supercomputer to process data – is a new model for UVA, and one that eases the learning curve for researchers who

  • Computing Systems

    UVA Research Computing can help you find the right system for your computational workloads. From supercomputers to HIPAA secure systems to cloud-based deployments with advanced infrastructure, various systems are available to researchers.
    Facilities Statement - Are you submitting a grant proposal and need standard information about UVA research computing environments? Get it here. High Performance Computing - Rivanna A traditional high performance cluster with a resource manager, a large file system, modules, and MPI processing. Get Started on Rivanna Secure Computing for Highly Sensitive Data - Ivy A multi-platform, HIPAA-compliant system for secure data that includes dedicated virtual machines (Linux and Windows), JupyterLab Notebooks, and Apache Spark.

  • Political Sentiment Analysis

    The nature of political communication has been fundamentally altered by the emergence of social media. In earlier eras, social scientists, journalists, and citizens could focus on static statements by politicians and candidates in order to understand the nature of political discourse. Social scientists studying political communication would design surveys and focus groups to understand which messages were received by citizens, and with what effect. Today, as news moves to digital platforms and as political figures increasingly rely on social media, political communication is fundamentally dynamic. Studying patterns of communication among politicians, their supporters, and their critics requires scholarly focus on the content, sentiment, and framing of posts on various social media platforms.
  • Pricing

    Below is a schedule of prices for Research Computing resources.
    Rivanna Allocations Type SU Limits Cost SU Lifetime Standard None Free 12 months Purchased None $0.01 Forever Instructional 100,000 Free 2 weeks after last teaching session About Allocations
    Storage Name Security Cost Research Project Standard $60 TB/year Research Standard Standard $45 TB/year ZFS Standard $30 TB/year – Ivy Central Storage High $45 TB/year Ivy NAS Storage High $60 TB/year – Storage Details Request Storage

  • ACCORD: Jupyter Lab

    Back to Overview
    Jupyter Lab allows for interactive, notebook-based analysis of data. A good choice for pulling quick results or refining your code in numerous languages including Python, R, Julia, bash, and others.
    Learn more about Jupyter Lab

  • ACCORD: RStudio

    Back to Overview
    RStudio is the standard IDE for research using the R programming language.
    Learn more about RStudio

  • ACCORD: Theia IDE

    Back to Overview
    Theia Python is a rich IDE that allows researchers to manage their files and data, write code with an intelligent editor, and execute code within a terminal session.
    Learn more about the Theia Python IDE

  • High Performance Computing

    Research Computing supports all UVA researchers who are interested in writing code to address their scientific inquiries. Whether these programming tasks are implemented interactively, in a series of scripts or as an open-source software package, services are available to provide guidance and enable collaborative development. RC has specific expertise in object oriented programming in Matlab, R, and Python.
    Examples of service areas include:
    Collaborating on package development Reviewing and debugging code Preparing scripts to automate or expedite tasks Developing web interfaces for interactive data exploration Advising on integration of existing software tools UVA has two local computational facilities available to researchers: Rivanna and Ivy.

  • Rivanna HPC Software

    Overview Research Computing at UVA offers a variety of standard software packages for all Rivanna users. We also install requested software based on the needs of the high-performance computing (HPC) community as a whole. Software used by a single group should be installed by that group’s members, ideally on leased storage controlled by the group. Departments with a set of widely-used software packages may install them to the lsp_apps space. The Research Computing group also provides limited assistance for individual installations.
    For help installing research software on your PC, please contact Research Software Support at res-consult@virginia.edu.
    Software Modules and Containers Software on Rivanna is accessed via environment modules or containers.

  • ACCESS: Advanced Cyberinfrastructure Coordination Ecosystem: Services and Support

    The NSF’s ACCESS (Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support) program builds upon the successes of the 11-year XSEDE project, while also expanding the ecosystem with capabilities for new modes of research and further democratizing participation. ACCESS Home:  access-ci.org  access-ci.org/about Allocations Allocations: allocations.access-ci.org Documentation Support: support.access-ci.org Community Engagement ACCESS: support.access-ci.org/affinity-groups Campus Champions: https://campuschampions.cyberinfrastructure.org UVa Research Computing has two Champions, Ed Hall and Katherine Holcomb For more help, please feel free to contact RC staff to set up a consultation or visit us during office hours.
  • XSEDE: Extreme Science and Engineering Development Environment

    XSEDE’s Mission was to substantially enhance the productivity of a growing community of scholars, researchers, and engineers through access to advanced digital services that support open research; and coordinate and add significant value to the leading cyberinfrastructure resources funded by the NSF and other agencies. — The XSEDE project ended on August 31, 2022 and was succeeded by the  ACCESS project.
    XSEDE Home:  www.xsede.org

  • Frequently Asked Questions

    General Do you have a general computing question?
    Read our FAQ› Rivanna High Performance Computing Platform
    Read our FAQ › Ivy Secure Data Computing Platform
    Read our FAQ › Storage Research Data Storage & Transfer
    Read our FAQ ›

  • Rivanna FAQs

    General Usage Allocations Research Software Job Management Storage Management Data Transfer Downloading Files Other Questions General Usage How do I gain access to Rivanna? A faculty or research staff member must first request an allocation on Rivanna. Full details can be found here.
    How do I log on to Rivanna? Use an SSH client from a campus-connected machine and connect to rivanna.hpc.virginia.edu. Instructions for using ssh and other login tools, as well as recommended clients for different operating systems, are here. You can also access Rivanna through our Web-based interface Open OnDemand or FastX.
    Off Campus? Connecting to Rivanna from off Grounds via Secure Shell Access (SSH) or FastX requires a VPN connection.

  • Graphical SFTP/SCP Transfer Tools

    Several options are available to transfer data files between a local computer and Rivanna through user-friendly, graphical methods.
    Off Campus? Connecting to Rivanna from off Grounds via Secure Shell Access (SSH) or FastX requires a VPN connection. We recommend using the UVA More Secure Network if available. The UVA Anywhere VPN can be used if the UVA More Secure Network is not available. Only Windows and Mac OSX operating systems are supported by the Cisco client provided by ITS. Linux users should refer to these unsupported instructions to install and configure a VPN. The More Secure Network requires authentication through Duo; users should follow the instructions on the dialog box to enter "

  • FastX Web Portal

    Overview FastX is a commercial solution that enables users to start an X11 desktop environment on a remote system. It is available on the Rivanna frontends. Using it is equivalent to logging in at the console of the frontend.
    Using FastX for the Web We recommend that most users access FastX through its Web interface. To connect, point a browser to:
    https://rivanna-desktop.hpc.virginia.edu
    Off Campus? Connecting to Rivanna from off Grounds via Secure Shell Access (SSH) or FastX requires a VPN connection. We recommend using the UVA More Secure Network if available. The UVA Anywhere VPN can be used if the UVA More Secure Network is not available.

  • Open OnDemand

    Overview Open OnDemand is a graphical user interface that allows access to Rivanna via a web browser. Within the Open OnDemand environment users have access to a file explorer; interactive applications like JupyterLab, RStudio Server & FastX Web; a command line interface; and a job composer and job monitor.
    Logging in to Rivanna Rivanna is accessible through the Open OnDemand web client at https://rivanna-portal.hpc.virginia.edu. Your login is your UVA computing ID and your password is your Netbadge password. Some services, such as FastX Web, require the Eservices password. If you do not know your Eservices password you must change it through ITS by changing your Netbadge password (see instructions).

  • Open OnDemand: File Explorer

    Open OnDemand provides an integrated file explorer to browse and manage small files. Rivanna has multiple locations to store your files with different limits and policies. Specifically, each user has a relatively small amount of permanent storage in his/her home directory and a large amount of temporary storage (/scratch) where large data sets can be staged for job processing. Researchers can also lease storage that is accessible on Rivanna. Contact Research Computing or visit the storage website for more information.
    The file explorer provides these basic functions:
    Renaming of files Viewing of text and small image files Editing text files Downloading & uploading small files To see the storage locations that you have access to from within Open OnDemand, click on the Files menu.

  • Open OnDemand: Job Composer

    Open OnDemand allows you to submit Slurm jobs to the cluster without using shell commands.
    The job composer simplifies the process of:
    Creating a script Submitting a job Downloading results Submitting Jobs We will describe creating a job from a template provided by the system.
    Open the Job Composer tab from the Open OnDemand Dashboard.
    Go to the New Job tab and from the dropdown, select From Template. You can choose the default template or you can select from the list.
    Click on Create New Job. You will need to edit the file that pops up, so click the light blue Open Editor button at the bottom.

  • Pulse Laser Irradiation and Surface Morphology

    Dr. Zhigilei and his team are using Rivanna to perform large-scale atomistic simulations aimed at revealing fundamental processes responsible for the modification of surface morphology and microstructure of metal targets treated by short pulse laser irradiation. The simulations are performed with a highly-optimized parallel computer code capable of reproducing collective dynamics in systems consisting of up to billions of atoms. As a result, the simulations naturally account for the complexity of the material response to the rapid laser energy deposition and provide clear visual representations, or “atomic movies,” of laser-induced dynamic processes. The mechanistic insights revealed in the simulations have an immediate impact on the development of the theoretical understanding of laser-induced processes and assist in optimization of laser processing parameters in current applications based on laser surface modification and nanoparticle generation in laser ablation.
  • Fluid Dynamics and Reef Health

    Professor Reidenbach and his team are using Rivanna to run computational fluid dynamics simulations of wave and tide driven flows over coral reefs in order to determine how storms, nutrient inputs, and sediments impact reef health. This is an image of dye fluxing from the surface of the Hawaiian coral Porites compressa utilizing a technique known as planar laser induced fluorescence (PLIF). Reefs such as this one have been severely impacted by human alteration, both locally through additional inputs of sediments and nutrients, and globally through increased sea surface temperatures caused by climate change. Reidenbach is hopeful that his computational models will allow scientists to better predict the future health of reefs based on human activity and improve global reef restoration efforts.
  • Economic Market Behavior

    While conducting research for a highly-technical study of market behavior, Dr. Ciliberto realized that he needed to parallelize an integration over a sample distribution. RC staff member Ed Hall successfully parallelized Ciliberto’s Matlab code and taught him how to do production runs on the University’s high-performance clusters. “The second stage estimator was computationally intensive,” Ciliberto recalls. “We needed to compute the distribution of the residuals and unobservables for multiple parameter values and at many different points of the distribution, which requires parallelizing the computation. Ed Hall’s expertise in this area was crucial. In fact, without Ed’s contribution, this project could not have been completed.
  • Tracking Bug Movements

    Ed Hall worked with the Brodie Lab in the Biology department, to set up a workflow to analyze videos of bug tracking experiments on the Rivanna Linux cluster. They wanted to use the community Matlab software (idTracker) for beetle movement tracking. Their two goals were to shorten the software runtime and to automate the process. There was a large backlog of videos to go through. Ed installed the idTracker software on Rivanna and modified the code to parallelize the bug tracking process. He wrote and documented shell scripts to automate their workflow on the cluster.
    PI: Edmund Brodie, PhD (Department of Biology)

  • Logging In

    Rivanna is accessible through a web portal, secure shell terminals, or a remote desktop environment. For of all of these access points, your login is your UVA computing ID and your password is your Eservices password. If you do not know your Eservices password you must change it through ITS.
    Off Campus? Connecting to Rivanna from off Grounds via Secure Shell Access (SSH) or FastX requires a VPN connection. We recommend using the UVA More Secure Network if available. The UVA Anywhere VPN can be used if the UVA More Secure Network is not available. Only Windows and Mac OSX operating systems are supported by the Cisco client provided by ITS.

  • MobaXterm

    MobaXterm is the recommended login tool for Windows users. It bundles a tabbed ssh client, a graphical drag-and-drop sftp client, and an X11 window server for Windows, all in one easy-to-use package. Some other tools included are a simple text editor with syntax coloring and several useful Unix utlities such as cd, ls, grep, and others, so that you can run a lightweight Linux environment on your local machine as well as use it to log in to a remote system.
    Download To download MobaXterm, click the link below. Select the “Home” version, “Installer” edition,
    Download MobaXterm
    Run the installer as directed.

  • Slurm Job Manager

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    Overview Rivanna is a multi-user, managed environment. It is divided into login nodes (also called frontends), which are directly accessible by users, and compute nodes, which must be accessed through the resource manager.

  • Quantifying Cerebral Cortex Regions

    A powerful new technique for quantifying regions of the cerebral cortex was developed by Nick Tustison and James Stone at the University of Virginia along with collaborators from the University of Pennsylvania. It was evaluated using large data sets comprised of magnetic resonance imaging (MRI) of the human brain processed on a high-performance computing cluster at the University of Virginia. By making this technique available as open-source software, other neuroscientists are now able to investigate various hypotheses concerning the relationship between brain structure and development. Tustison’s and Stone’s software has been widely disseminated and is being actively incorporated into a variety of clinical research studies, including a collaborative effort between the Department of Defense and Department of Veterans Affairs, exploring the long term effects of traumatic brain injury (TBI) among military service members.
  • Rivanna HPC Software

    Overview Research Computing at UVA offers a variety of standard software packages for all Rivanna users. We also install requested software based on the needs of the HPC community as a whole. Software used by a single group should be installed by that group’s members, ideally on leased storage controlled by the group. Departments with a set of widely-used software packages may install them to the lsp_apps space. The Research Computing group also provides limited assistance for individual installations.
    For help installing research software on your PC, please contact Research Software Support at res-consult@virginia.edu.
    Software Modules and Containers Software on Rivanna is provided via environment modules or as containers.

  • Rivanna Software List

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  • Software Modules

    The lmod modules system on Rivanna enables users to easily set their environments for selected software and to choose versions if appropriate.
    The lmod system is hierarchical; not every module is available in every environment. We provide a core environment which contains most of the software installed by Research Computing staff, but software that requires a compiler or MPI is not in that environment and a compiler must first be loaded.
    View All Modules   Basic Commands List all available software
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  • What is Research Computing?

    UVA Research Computing (RC) is a new program that aims to support computational biomedical research by providing advanced cyberinfrastructure and expertise in data analysis at scale. Our mission is to foster a culture of computational thinking and promote interdisciplinary collaboration in various data-driven research domains. We offer services related to high performance computing, cloud architecture, scientific programming and big data solutions. We also aim to promote computationally intensive research at UVA through collaborative efforts such as UVA’s own CADRE (Computation And Data Resource Exchange) and XSEDE (Extreme Science and Engineering Discovery Environment).
    One of our driving philosophies is that researchers already have medical and scientific expertise, and should not have to become computing experts on top of that.

  • User Guides

    High Performance Computing Standard and high security HPC to run your code, generally written in R, Python or shell scripts.
    Get Started › Secure Computing Secure virtual machines and interactive notebooks for processing HIPAA and other highly sensitive data.
    Get Started › Storage Need large, or extremely large storage offsite or on grounds? Can you count in GB, TB, or PB? Learn more about storage options and pricing.
    Get Started › Cloud Have an idea you’d like to test? Need an environment provisioned in short-order? We can help you build in the AWS cloud.

  • Computing Environments at UVA

    Research Computing (UVA-RC) serves as the principal center for computational resources and associated expertise at the University of Virginia (UVA). Each year UVA-RC provides services to over 433 active PIs that sponsor more than 2463 unique users from 14 different schools/organizations at the University, maintaining a breadth of systems to support the computational and data intensive research of UVA’s researchers. High Performance Computing  UVA-RC’s High Performance Computing (HPC) systems are designed with high speed networks, high performance storage, GPUs, and large amounts of memory in order to support modern compute and memory intensive programs. UVA-RC’s HPC systems are comprised of over 614 compute nodes, with a total of 20476 X86 64-bit compute cores and 240 TB total RAM.