QCL Computational Resources
High Performance Computing (HPC)
XSEDE Supercomputing Allocations
XSEDE (Extreme Science and Engineering Discovery Environment) is the most advanced, powerful, and robust collection of integrated advanced digital resources and services in the world. QCL has two Campus Champions who are trained to help local users utilize supercomputing resources available through the XSEDE program. QCL awarded over 350,000 Service Units (SUs) from various national supercomputing facilities. The Service Unit (SU) is like a currency used to run an application on supercomputers. Supercomputer users are charged by SUs (hours of runtime on one core). For example, if an application ran on 100 cores for 10 hours, 1,000 SUs will be deducted from your account.
XSEDE Campus Champion Allocations (As of December 2020)
| Name | Facility | Type | SU (Core hours) |
|---|---|---|---|
| Comet | SDSC | Cluster | 50000 |
| Jetstream | Indiana U | Cluster | 50000 |
| Bridges | PSC | Cluster | 50000 |
| Bridges Large | PSC | Cluster | 1000 |
| Bridges Pylon | PSC | Cluster | 500 |
| Bridges GPU | PSC | Cluster/GPU | 2500 |
| Stampede2 | TACC | Cluster | 1600 |
| Oasis | SDSC | Storage | 500 |
| Ranch | TACC | Storage | 500 |
| Comet GPU | SDSC | Cluster/GPU | 2500 |
| OSG | Multiple | Virtual Cluster | 200000 |
The Campus Champion allocations can be used to test computational research applications. To test out the supercomputers, please make an appointment with one of the Campus Champions (email: theqcl@cmc.edu).
NVIDIA GPGPU Machine
A GPGPU (General Purpose Graphic Processing Unit) machine is a high performance computer system equipped with one or more GPUs. QCL has an NVIDIA DGX system having four Tesla V100 GPUs.
| GPUs | 4X Tesla V100 |
| TFLOPS (Mixed precision) | 500 |
| GPU Memory | 128 GB total system |
| NVIDIA Tensor Cores | 2,560 |
| NVIDIA CUDA Cores | 20,480 |
| CPU | Intel Xeon E5-2698 v4 2.2 GHz (20-Core) |
| System Memory | 256 GB RDIMM DDR4 |
| Data Storage | Data: 3X 1.92 TB SSD RAID 0 |
| OS Storage | OS: 1X 1.92 TB SSD |
| Network | Dual 10GBASE-T (RJ45) |
RStudio Server
https://webapps.cmc.edu/rstudio
We have a dedicated server machine for RStudio. Students taking a CMC course using R and a QCL workshop can get access. To get access to the RStudio Server, please contact qcl@cmc.edu for your account activated.
The RStudio Server is equipped with 2 CPUs (32 cores) and 512 GB of memory. So, it will perform better than your laptop or personal computer (for sure!) for those who need large memory space.