COR@L Lab is the computational software system in Lehigh University Industrial and Systems Engineering Department.
| Sl. No. | Name | Memory (MB) | CPU | Scratch | Operating System | Remarks |
|---|---|---|---|---|---|---|
| 01 | coral | 4000 | Intel Xeon 3.10GHz (4 cores) | – | Debian 10 | webserver, mailman, bugzilla, mysql, trac, subversion. 64 bit |
| 02 | polyp1 (polyps) | 32000 | AMD Opteron 2.0 GHz (16 cores) | 761GB | Debian 12 | 64 bit architecture, head node / login node |
| 03 | polyps (2-15) | 32000 | AMD Opteron 2.0 GHz (16 cores) | 761GB | Debian 12 | 64 bit architecture, head node: polyp1 |
| 04 | polyps (30) | 128000 | Intel Xeon 2.4GHz (24 cores) | 92GB | Debian 12 | 64 bit architecture, Tesla K80 GPGPU, head node: polyp1 |
| 05 | beluga | 11000 | Intel Xeon 3.2GHz (4 cores) | – | Debian 8 | 64 bit architecture, storage node, exports home, software, and globalscratch directories |
| 06 | shark | 2000 | Intel Xeon 2.4GHz (2 cores) | 250GB | Ubuntu 14.04 | Software licences. |
Access to polyp30 is accessible via PBS. Please use an interactive job to (qsub -I) to gain access to its resources. Once you have a job, you can submit your batch job to that node. It has Nvidia Tesla K80 GPGPU. Currently it has in /usr/local the following versions of cuda installed:
user@polyp30:~$ cd /usr/local user@polyp30:/usr/local$ ls -al |grep cuda drwxr-sr-x 17 root staff 4.0K Jun 26 2016 cuda-7.5 drwxr-sr-x 8 root staff 4.0K Oct 10 2017 cuda-8.0 drwxr-sr-x 19 root staff 4.0K Mar 26 2018 cuda-9.1 drwxr-sr-x 18 root staff 4.0K Mar 27 2018 cuda-9.0 drwxr-sr-x 18 root staff 4.0K Dec 16 2024 cuda-10.2 lrwxrwxrwx 1 root staff 21 Jul 22 08:06 cuda -> /usr/local/cuda-11.4/ drwxr-sr-x 16 root staff 4.0K Jul 22 08:08 cuda-11.4
Please update your PATH (echo $PATH) and any other variables to utilize the version you need. (LD_LIBRARY_PATH, PYTHONPATH).
nVidia ended Cuda support for the K80 GPGPU with Cuda 11.4. Newer versions will not function with this GPGPU.
Support for the following compute capabilities are deprecated in the CUDA 11.0 Toolkit:
sm_35 (Kepler)
► sm_37 (Kepler) ◄
sm_50 (Maxwell)
See matrix link above
* CUDA Toolkit v11.0.3 Release Notes
1. Due to the heavy usage of the login node (polyps / polyp1), it is recommended you launch an interactive job on a compute node. This will provide you the dedicated resources you request rather than running on a shared node.