Research Computing (RC) continually updates its policies in response to changing user demands, system requirements, and security compliance. As a result of new security protocols issued by the Office of Audit and Compliance, we are no longer able to offer Ivy users direct access to the system through HIT’s Secure Clinical Network (SCN). Effective 12/11/19: All users will need Duo Mobile multi-factor authentication (MFA) and a High Security (HSZ) VPN connection to login to Ivy. Current VPN users will not be affected by this change, but are advised to migrate to the HSZ VPN and Duo prior to 12/3/19 when Information Technology Services (ITS) will permanently retire UVA Identity Tokens and the Joint Virtual Private Network (JVPN).
RC system engineers will begin actively clearing /scratch files more than 90 days old beginning 10/14/2019. /scratch is intended as a temporary work directory (90 days maximum). It is not backed up and needs to be purged periodically in order to maintain a stable HPC environment. We encourage users to back up their important data. RC offers several low-cost storage options to researchers.
For more information about research computing storage options:
Visit our Storage Overview page. Learn more about specific storage features of Rivanna HPC. What is /scratch and why should you use it?
RC staff are teaching a series of free hands-on workshops this fall that are open to all UVA researchers. Space is limited, so register today! Topics include:
Image Processing with Fiji/ImageJ (Sept 11) MATLAB Fundamentals (Sept 12) Programming in MATLAB (Sept 19) Optimizing R Code (Sept 24) Parallel Computing in MATLAB (Sept 26) Introduction to Parallel R (Oct 1) Machine Learning with MATLAB (Oct 3) Automation of Image Processing with Fiji/ImageJ (Oct 9) Imagining Data Mangement with OMERO (Oct 16) Deep Learning with MATLAB (Oct 17) Moving R Programs to Rivanna (Oct 17) Register through the new CADRE Academy portal.
UVA Research Computing strives to empower researchers to achieve more through the use of cutting-edge computational resources. This has led to fruitful collaborations with researchers and staff across grounds, including these groups and departments:
Astronomy Biochemistry and Molecular Genetics Biomedical Engineering Center for Applied Biomechanics Center for Advanced Medical Analytics Center for Behavioral Health and Technology Center for Diabetes Technology Center for Public Health Genomics Economics Emergency Medicine Environmental Sciences Infectious Diseases Public Health Sciences Materials Science & Engineering Pediatrics–Neonatology Radiology and Medical Imaging Surgery UVA Sinklab To browse a gallery of recent projects, visit our Projects page below.
RC staff are teaching a series of free hands-on workshops this summer that are open to all UVA researchers. Space is limited, so register today! Topics include:
Programming in Python (June 3-June 5) R (June 3-June 4) MATLAB (June 5-June 7 and June 13) Compiled Languages, C++ and Fortran (June 6-June 7) Scientific Image Processing with Fiji/ImageJ (June 10) Introduction to High-Performance Computing (June 10) Software Design and Testing (June 11) HPC Data Analytics (June 11) Parallel Programming Using MPI (June 12-June 13) Bioinformatics (June 12) Scientific Visualization (June 14) OpenMP and Accelerators (June 14) Register through the new CADRE Academy portal.
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.