SPORC (Scheduled Processing On Research Computing) is Research Computing's High Performance Computing (HPC) cluster. An HPC cluster is a collection of connected computers coordinated to perform tasks with high efficiency. SPORC is specially made to assist researchers in expediting the process of collecting and analyzing data with its computational power. A more in-depth look at SPORC can be found on the SPORC - Overview wiki page.
64 SuperMicro X11 systems with space for 4 GPU cards
16 Nvidia V100 cards
48 Nvidia P4 cards
100 Nvidia A100 cards
Our large single-system image (SSI) compute node, affectionately referred to as "the Ocho", is a node in SPORC.
SYS-7089P Supermicro 8-way
192 cores (Intel® Xeon® Platinum 8168 CPU @ 2.70GHz)
3.06 TB RAM
1 Nvidia V100 card
Research Computing will have regularly scheduled maintenance during the first Thursday of every month starting at 0800 EST and ending at midnight. These outage windows may or may not be utilized at the discretion of the RC support staff and will generally not require the entire allotted time. Some and/or all services may be unavailable during the window. SLURM jobs will be prevented from scheduling if the requested run time will run into scheduled maintenance. If we have to perform unscheduled maintenance due to security or service failure we will update the "message of the day" (motd) and/or email users as deemed appropriate. To get a listing of the next scheduled maintenance date use the command time-until-maintenance.
We currently offer numerous applications useful for gathering and analyzing data. A large number of research topics have applications that would assist in the researching process. The following is a sample of applications we currently provide for researchers. To see all the software available, log onto SPORC and type module avail into the command line. More information on what this means and how to use modules can be found on the Using Modules page. For more applications provided by us and their respective documentation see Instructions.
Comsol - interactive environment for modeling and simulating scientific and engineering problems
MATLAB - create models and applications, develop algorithms, analyze data
Torch- open-source machine learning
High Throughput Computing (HTC)
High Throughput Computing (HTC) splits large jobs into much smaller, simpler tasks. These jobs are run in parallel on SPORC which allows for data to be collected more efficiently and for researchers to receive their results quicker. Our HTC service gives researchers access to large amounts of computational power and high-quality resources which can be shared among their group, allowing for collaboration. Researchers are able to manage their jobs, check the status of each job, and see the availability of resources.
Accelerator Assisted Compute
An accelerator is a hardware device or software program whose purpose is to enhance the overall performance of the computer. The hardware accelerator works by performing functions with its own custom logic faster than the CPU. With this, the time taken to perform specific jobs is cut down significantly and the CPU is unburdened to perform other tasks. For researchers this means that, by utilizing accelerators, you can get results for your research faster.
Research Computing will help researchers develop a cloud computer environment tailored to the researcher's needs. Assistance is provided to help researchers utilize cloud services and tools so that research data can be collected, stored, and analyzed in an efficient way.
Virtual Hosting Services
Virtual Hosting is when a physical server is divided into multiple isolated virtual environments by a software application. RIT schools, departments, researchers, or any other member of RIT can request virtualized hosting services for a new project or application, a new service, new portions or an existing environment, or for a hosting platform. Guest hosting services are also available for research and administrative applications.
Citation & Acknowledgement
If Research Computing helped you complete your published work, please acknowledge us and use the citation below. Acknowledgment helps us grow and continue to support more researcher's in their quest to discover. Feel free to include specifics as to how we helped you. The following is an example:
The authors acknowledge Research Computing at the Rochester Institute of Technology for providing computational resources and support that have contributed to the research results reported in this publication.