HPC 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.

Get Started

Get Access / Allocations

Request access to Rivanna HPC for your research. Add collaborators to your project.

Logging In

How do you log in? Need to use a web browser or a shell command-line? Learn how.

File Transfer

How to move files? How to move large datasets to the HPC cluster? Learn how.


Find and run software suited for your HPC jobs. Learn how to load and use modules.


Learn about the vaious storage options within Rivanna: for users, groups, and temporary.

Running Jobs in SLURM

Your code is ready. Your data is in place. Learn how to run your jobs across the cluster, and other advanced SLURM features.


Learn the right queue (or "partition") for running your job, such as standard, parallel, gpu, and more.

Usage Policies

Understand what is expected of you as a Rivanna HPC user. All users must comply with these requirements.


Have a question? Others may have asked it before, so please check our Frequently Asked Questions page first.

System Details

Rivanna is a managed resource; users must submit jobs to queues controlled by a resource manager, also known as a queueing system. The manager in use on Rivanna is SLURM. SLURM refers to queues as partitions because they divide the machine into sets of resources. There is no default partition and each job must request a specific partition. Partitions and access policies are subject to change, but the following table shows the current structure. Note that memory may be requested per core or for the overall job. If the total memory required for the job is greater than the number of cores requested multiplied by the maximum memory per core, the job will be charged for the additional cores whether they are used or not. In addition, jobs running on more than one core may still require a request of total memory rather than memory per core, since memory per core is enforced by the system but some multicore software packages (ANSYS, for example) may exceed that for a short time even though they never exceed cores x memory/core.
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 1.00
gpu 3 days 4 8 12GB 240GB 2.00
knl 3 days 8 512 cores/2048 threads 3 GB (per physical core) 192GB 1.00
dev 1 hour 2 8 6GB 36GB 0.00
Cores/node RAM/node Nodes
20 128GB 195
28 256GB 25
40 384GB 80
16 1TB 5
28+8 K80 GPU 256GB 8
28+4 P100 GPU 256GB 4
28+4 V100 GPU 256GB 1
64 Knight's Landing 196GB 8

Usage Policies

Research computing resources at the University of Virginia are for use by faculty, staff, and students of the University and their collaborators in academic research projects. Personal use is not permitted. Users must comply with all University policies for access and security to University resources. The HPC system has additional usage policies to ensure that this shared environment is managed fairly to all users. UVA’s Research Computing (RC) group reserves the right to enact policy changes at any time without prior notice.


Exceeding the limits on the frontend will result in the user’s process(es) being killed. Repeated violations will result in a warning; users who ignore warnings risk losing access privileges.

Standard Partition

Each job in the standard queue is restricted to a single node. Users may submit multiple jobs or job arrays, but the maximum aggregate cpu cores allowed for a single user’s running jobs is 1000.

Parallel Partition

Users must request a minimum of two nodes and four cpu cores (and no more than 900 cpu cores) when submitting a job to the parallel queue.

Software Licenses

Excessive consumption of licenses for commercial software, either in time or number, if determined by system and/or RC staff to be interfering with other users’ fair use of the software, will subject the violator’s processes or jobs to termination without warning. Staff will attempt to issue a warning before terminating processes or jobs but inadequate response from the violator will not be grounds for permitting the processes/jobs to continue.

Inappropriate Usage

Any violation of the University’s security policies, or any behavior that is considered criminal in nature or a legal threat to the University, will result in the immediate termination of access privileges without warning.