UVA Research Computing

Research Computing

Creating innovative solutions for researchers


  • Rivanna Maintenance, December 18

    Rivanna will be taken down for routine maintenance on Wednesday, December 18, beginning at 6 a.m. You may continue to submit jobs until the maintenance period begins, but if the system determines your job will not have time to finish, it will not start until Rivanna is returned to service. Rivanna is expected to return to service by 6 a.m. on Thursday, December 19.
  • JIRA Downtime, December 13

    The JIRA ticketing system will be taken offline on Friday, December 13 from 6 p.m. to 9 p.m. while our system engineers continue the process of migrating the ticketing system from a local environment to the cloud. Please avoid submitting requests during this period if possible. Although moving to a cloud-based ticketing system will improve the speed and efficiency of our customer service in the long run, in the short-term it may cause disruptions for some users. If you are unable to login to JIRA after the migration is completed, you will need to change your password using your UVA e-mail address.
  • Globus Data Transfer

    Globus Data Transfer Is a simplified way to access and move your research data, across all systems, using any existing identity. Transfer data to and from systems such as: Laptops HPC clusters (Rivanna) Secure computing (Ivy) Lab / departmental storage Tape archives Cloud storage Off-campus resources (XSEDE, National Labs) Access them all using just a web browser. This can help you share research data with colleagues, co-investigators, or to move data back and forth between a lab workstation and Rivanna or your personal computer. Data stored at a different institution? At a supercomputing facility? All you need is your campus login.
  • Research Value Storage

    Overview Research Computing offers several budget options for storing non-sensitive research data. The Research Value Storage provides users with a solution for research data storage and collaboration. Members in the same group have access to a shared directory created by the team lead or PI. Group membership can be defined and managed through ITS MyGroups system. Value storage is mounted on the Rivanna HPC cluster and can also be accessed on a personal computer with an SMB mount, allowing for point-and-click file manipulation. If you are not a researcher, UVA ITS offers Academic Value storage for long-term storage of large scale data.
  • Non-Sensitive Data Storage

    /home /home is a free 50GB space provided to users of the Rivanna HPC system and is visible from the Rivanna login and compute nodes. /home is the default working directory when logging on to Rivanna. Users can also access their home directory at /home/$USER, where $USER is an individual’s UVa computing ID. /scratch /scratch is a Lustre high performance parallel filesystem accessible via the Rivanna login and compute nodes. All Rivanna HPC users are granted 10TB for free and can access this space within Rivanna at /scratch/$USER, where $USER is an individual’s UVa computing ID. The /scratch directory is not intended for long-term data storage.
  • Important Notes from the 17 September Rivanna Maintenance

    Learn about recent changes implemented during the Sept. 17, 2019 maintenance.
  • Computing Environments at UVA

    Rivanna The primary vehicle for high-performance computing since 2014 has been the Rivanna cluster. Rivanna is a heterogenous system consisting of approximately 186 x 20-core nodes with 128GB of RAM each, 25 x 28-core nodes with 256 GB of RAM, and 152 x 40-core nodes with 384GB each. Five “big memory” nodes offer 1TB of RAM with 16 cores each. All nodes are supported by a high-performance FDR Infiniband network using Mellanox hardware and some have EDR Infiniband. A number of nodes supporting specialty hardware are included; there are 8 nodes with NVIDIA K80 GPGPUs, 4 nodes with NVIDIA V100 GPGPUs, 1 node with NVIDIA V100, and 2 nodes with NVIDIA RTX2080TI boards.
  • 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. 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 job scheduler, large file system, modules, and MPI processing. Get Started on Rivanna
    Secure Computing for 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.

  • HPC Storage

    There are a variety of options for storing large-scale research data at UVa. Non-sensitive data storage systems can be accessed from the Rivanna high performance computing system. .tg {border-collapse:collapse;border-spacing:0;border-color:#ccc;} .tg td{font-family:Arial, sans-serif;font-size:14px;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#fff;} .tg th{font-family:Arial, sans-serif;font-size:14px;font-weight:normal;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#f0f0f0;} .tg .tg-hy9w{background-color:#eceeef;border-color:inherit;vertical-align:top} .tg .tg-dc35{background-color:#f9f9f9;border-color:inherit;vertical-align:top} .tg .tg-0qmj{font-weight:bold;background-color:#eceeef;border-color:inherit;vertical-align:top} Non-Sensitive Data Storage Name Quota Price Data Protection Accessible from Best Practices /home 50GB Free 3-week snapshot Rivanna login and compute nodes /home is best used as a working directory when using Rivanna interactively. SLURM jobs run against /home will be slower than those run against /scratch. /scratch 10TB Free Data removed 90 days after last file modification timestamp Rivanna login and compute nodes /scratch is a high performance parallel filesystem that is suitable for large scale computational work.
  • 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 01/30/20 Using Rivanna from the Command Line Gladys Andino 01/31/20 Fundamentals of Matlab Ed Hall 02/06/20 Parallel Computing with Matlab Ed Hall 02/11/20 Shiny Web Apps in R Christina Gancayco 02/13/20 Software Containers for HPC Environments Ruoshi Sun 02/13/20 Statistical Methods in Matlab Ed Hall 02/18/20 Intro to Image Processing with Fiji/ImageJ Karsten Siller 02/19/20 Moving R to HPC Jackie Huband 02/20/20 High Performance Python Karsten Siller 02/20/20 Optimization Methods in Matlab Ed Hall 02/25/20 Automation of Image Processing with Fiji/ImageJ Karsten Siller 02/26/20 Optimizing R Code Jackie Huband 02/27/20 C/C++ and Fortran on Rivanna Ruoshi Sun 02/27/20 Deep Learning in Matlab Christina Gancayco 03/04/20 Parallelizing R Jackie Huband 03/05/20 Image Processing in Matlab Christina Gancayco 03/18/20 Parallel R with MPI Jackie Huband 03/26/20 Julia on Rivanna Ed Hall View All Upcoming Workshops on CADRE Academy ↗]() – View All Upcoming Workshops
  • Rivanna FAQs

    General Usage Allocations Applications Job Management Storage Management Data Transfer 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 use FastX. If you are off Grounds you must use the UVA Anywhere VPN. How do I reset my current password / obtain a new password?
  • 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 over 8,000 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. The sections below contain important information for new and existing Rivanna users. Please read each carefully. New users are invited to attend one of our free orientation sessions (“Introduction to the HPC System”) held throughout the year during office hours or by appointment.
  • 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 Login Screen After entering your computing ID and Netbadge password, you will see a launch screen. Launch In this example, we have no pre-existing sessions so we must create one. Click the Launch Session button. This will bring up a screen showing the options.
  • 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.
  • 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.
  • Rivanna Queues

    Several queues (or “partitions”) are availble to users for different types of jobs. One queue is restricted to single-node (serial or threaded) jobs; another for multinode parallel programs, and others are for access to specialty hardware such as large-memory nodes or nodes offering GPUs. Partition Max time per job Max nodes per job Max cores per job Max memory per core Max memory per node per job SU Charge Rate standard 7 days 1 40 12GB 375GB 1.00 parallel 3 days 45 900 6GB 120GB 1.00 largemem 4 days 1 16 62GB 975GB 1.
  • 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.
  • 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.
  • 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.
  • Pricing

    Below is a schedule of prices for Research Computing resources. Rivanna Allocations Type SU Limits Cost SU Lifetime Standard 100,000 per application; renewable up to 3x per year (400,000 total SUs) Free 12 months Deans’ Allocations None Free 12 months by default, negotiable Purchased None $0.015 (<1M SUs); $0.01 (=1M SUs) Forever Instructional 25,000 Free 2 weeks after last teaching session * GPU node charge rate is 2.0 SUs instead of 1.0. ** Non-UVA personnel are charged at a rate of $0.07/SU About Allocations
  • 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.
  • Allocations

    Time on Rivanna is allocated as Service Units (SUs). One SU corresponds to one core-hour. Multiple SUs make up what is called an allocation (e.g., a new allocation = 100K SUs). Allocations are managed through MyGroups groups that are automatically created for Principal Investigators (PIs) when they submit an allocation request. All UVA faculty, staff, and postdoctoral associates are considered PIs and therefore eligible for an allocation on Rivanna. Students—both graduate and undergraduate—cannot request allocations, but they are allowed to use Rivanna as members of a MyGroups group controlled by a PI. Eligibility and Account Creation University of Virginia tenure stream and academic general faculty, research faculty, research scientists, and postdoctoral associates may request any type of allocation.
  • 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? All users who wish to access Rivanna while off Grounds must use the UVA Anywhere VPN client. Only Windows and Mac OSX operating systems are supported. Linux users should refer to these unsupported instructions to install and configure a VPN. Web-based Access Open OnDemand is a graphical user interface that allows access to Rivanna via a web browser.
  • 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

    Overview Rivanna is a multi-user, managed environment. It is divided into frontends, which are directly accessible by users, and compute nodes, which must be accessed through the resource manager. We use the Simple Linux Utility for Resource Management (SLURM), an open-source tool that performs cluster management and job scheduling for Linux clusters. Jobs are submitted to the resource manager, which queues them until the system is ready to run them. SLURM selects which jobs to run, when to run them, and how to place them on the compute node, according to a predetermined site policy meant to balance competing user needs and to maximize efficient use of cluster resources.
  • Active Galactic Nuclei

    Some galaxies have an extremely energetic central region known as an Active Galactic Nucleus. These regions are among the brightest objects in the universe, often outshining all of the stars in their home galaxy combined. In at least some cases, the power source at the center of these extraordinary nuclei is actually a black hole; as gases are drawn toward the black hole, they spiral around it, generating gravitational energy that is converted into heat and electromagnetic waves. A simulation created by Prof. John Hawley (CLAS) with collaborators from Johns Hopkins University reveals this process at an unprecedented level of detail.
  • Research Data Storage

    There are a variety of options for storing large-scale research data at UVA. Non-sensitive data storage systems can be accessed from the Rivanna high performance computing system. Sensitive data can be stored and accessed within the Ivy secure computing environment. Information Technology Services (ITS) also provides multiple tiers of data storage for personal and non-research storage needs. .tg {border-collapse:collapse;border-spacing:0;border-color:#ccc;} .tg td{font-family:Arial, sans-serif;font-size:14px;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#fff;} .tg th{font-family:Arial, sans-serif;font-size:14px;font-weight:normal;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#f0f0f0;} .tg .tg-hy9w{background-color:#eceeef;border-color:inherit;vertical-align:top} .tg .tg-dc35{background-color:#f9f9f9;border-color:inherit;vertical-align:top} .tg .tg-0qmj{font-weight:bold;background-color:#eceeef;border-color:inherit;vertical-align:top} Non-Sensitive Data Storage Name Quota Price Data Protection Accessible from Best Practices Project Storage 1TB increments $60 /TB/yr 2 week snapshots Rivanna, NFS mount /projectis ideal for long-term storage of data to be accessed from Rivanna.
  • 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.
  • Compilers on Rivanna

    Rivanna offers multiple compiler bundles for C, C++, and Fortran. Different compilers have different strengths and weaknesses and different error messaging and debugging features, so users should be willing to try another one when appropriate. The modules system manages the compiler environment and ensures that only compatible libraries are available for loading. Many users of compiled languages are working with codes that can employ MPI for multinode parallel runs. MPI users should first understand how their chosen compiler works, then see the MPI instructions at our parallel programming page. Compiled languages can be more difficult to debug, and the assistance of a good debugger can be essential.
  • Machine Learning on Rivanna

    Overview Many machine learning packages can utilize general purpose graphics processing units (GPGPUs). If supported by the respective machine learning framework or application, code execution can be manyfold, often orders of magnitude, faster on GPU nodes compared to nodes without GPU devices. Rivanna has several nodes that are equipped with GPU devices. These nodes are available in the GPU partition. Access to a GPU node and its GPU device(s) requires specific SLURM directives or command line options as described in the Jobs using a GPU Node section. Applications Several machine learning software packages are installed on Rivanna. The most commonly used ones are:
  • Message Passing Interface (MPI) on Rivanna

    Overview MPI stands for Message Passing Interface. The MPI standard is defined by the Message Passing Interface Forum. The standard defines the interface for a set of functions that can be used to pass messages between processes on the same computer or on different computers. MPI can be used to program shared memory or distributed memory computers. There is a large number of implementations of MPI from various computer vendors and academic groups. MPI is supported on the Rivanna cluster. MPI On Rivanna MPI is a standard that describes the behavior of a library. It is intended to be used with compiled languages (C/C++/Fortran).
  • PyTorch on Rivanna

    Description PyTorch is an open source Python package to create deep learning networks. The latest PyTorch versions are now provided as prebuilt Singularity containers on Rivanna. The basic concept of running Singularity containers on Rivanna is described here. Similar to other popular deep learning frameworks like TensorFlow, Theano and CNTK, computations supported by the PyTorch package can be accelerated on general purpose graphics processing units (GPUs). All PyTorch container images provided on Rivanna require access to a GPU node. Access to GPU nodes is detailed in the sections below. PyTorch on Rivanna We maintain the PyTorch packages as Singularity containers on a public web portal, Singularity-Hub.
  • Rivanna Software List

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  • Software Containers

    Overview Containers bundle an application, the libraries and other executables it may need, and even the data used with the application into portable, self-contained files called images. Containers simplify installation and management of software with complex dependencies and can also be used to package workflows. Singularity is a container application targeted to multi-user, high-performance computing systems. It interoperates well with SLURM and with the Lmod modules system. Singularity can be used to create and run its own containers, or it can import Docker containers. Creating Singularity Containers To create your own image from scratch, you must have root privileges on some computer running Linux (any version).
  • 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 in the core environment: module avail Use “module spider” to find all possible modules. module spider module spider hdf5 If a version is specified to spider, it will indicate how to load that version.
  • TensorFlow on Rivanna

    Overview TensorFlow™ is an open source software library for high performance numerical computation. It has become a very popular tool for machine learning and in particular for the creation of deep neural networks. The latest TensorFlow versions are now provided as prebuilt Singularity containers on Rivanna. The basic concept of running Singularity containers on Rivanna is described here. TensorFlow code is provided in two flavors, either with or without support of general purpose graphics processing units (GPUs). All TensorFlow container images provided on Rivanna require access to a GPU node. Access to GPU nodes is detailed in the sections below.
  • Tools for Research

    Tools and software projects that UVA Research Computing has collaborated on:

    LOLAweb LOLAweb is a web server and interactive results viewer for enrichment of overlap between a user-provided query region set (a bed file) and a database of region sets. It provides an interactive result explorer to visualize the highest ranked enrichments from the database. LOLAweb is a web interface to the LOLA R package. Launch LOLAweb
    BARTweb There are a number of commercially licensed tools available to UVa researchers for free. These products, including UVa Box, Dropbox (Health System) and CrashPlan, are most suitable for small-scale storage needs.

  • Sensitive Data Storage - Ivy

    Overview The Ivy secure computing environment meets both HIPAA- and CUI-compliance standards and is ideal for storing sensitive research data. Ivy offers several storage options to fit your research computing needs. Ivy Central Storage Ivy Central Storage (ICS) is a sensitive data parking zone and central storage pool with a capacity greater than 1PB. This storage space is available for researchers with highly sensitive data and can be mounted on an Ivy virtual machine (VM). For added security, files stored on ICS are read & write only. Executable files can be moved from ICS to VM storage. Researchers can request space on ICS by first requesting an Ivy account using the form on the CADRE website.
  • /project Storage

    Overview The /project file system provides users with a collaborative space for data storage and sharing. Members in the same group have access to a shared directory created by the team lead or PI. Group membership can be defined and managed through ITS MyGroups system. /project storage is mounted on the Rivanna HPC cluster and runs on a new scale-out NAS file system. How to request space in /project /project storage is available by request (via CADRE User Support page) for $90/TB/YR. When filling out the form, the PI can specify the size of the /project directory and the name of an existing or new MyGroup that can access this space.
  • 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.
  • Bioinformatics Resources on Rivanna

    UVA research community has access to numerous bioinformatics software installed and ready-to-use on Rivanna. They are all available via the LMod module system. In addition, Click here for a comprehensive list. Popular Bioinformatics Software Below are some popular tools and useful links for their documentation and usage: .tg {border-collapse:collapse;border-spacing:0;border-color:#ccc;} .tg td{font-family:Arial, sans-serif;font-size:14px;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#fff;} .tg th{font-family:Arial, sans-serif;font-size:14px;font-weight:normal;padding:10px 5px;border-style:solid;border-width:0px;overflow:hidden;word-break:normal;border-color:#ccc;color:#333;background-color:#f0f0f0;} .tg .tg-hy9w{background-color:#eceeef;border-color:inherit;vertical-align:middle;} .tg .tg-dc35{background-color:#f9f9f9;border-color:inherit;vertical-align:middle;} .tg .tg-hy9w-nw{background-color:#eceeef;border-color:inherit;vertical-align:middle;white-space:nowrap;} .tg .tg-dc35-nw{background-color:#f9f9f9;border-color:inherit;vertical-align:middle;white-space:nowrap;} .tg .tg-0qmj{font-weight:bold;background-color:#eceeef;border-color:inherit;vertical-align:middle;} .scroll thead, .scroll tbody {display: block} .scroll tbody {overflow-y: auto; height: 500px;} .scroll thead tr:after {content: “;overflow-y: scroll; visibility: hidden; height: 0;} Tool Version Description Useful Links BEDTools 2.
  • Bioinformatics User Guides

    Bioinformatics on Rivanna UVA’s High-performance Computing Cluster All faculty, research staff and graduate students of UVA have access to Rivanna, university’s high-performance computing system with 290+ compute nodes (6500+ cores) for high-throughput multithreaded jobs, parallel jobs as well as memmory intensive large-scale data analyses. The architecture is specifically suited for large scale distributed genomic data analysis, with 100+ bioinformatics software packages installed and ready to use. Learn more Bioinformatics using FireCloud FireCloud Home
  • 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 HPC facilities available to researchers: Rivanna and Ivy.