...
| Login Nodes (l001, l002) | Compute Nodes (c001-c026) | High Memory Nodes (b001,b002) | GPU Nodes (g001, g002) | ||
|---|---|---|---|---|---|
INCLINE has three login nodes. When you first log in, you will be on one of the first two nodes. For example,
user "hostname" is on the first login node. It is important to remember that the login nodes are shared between all users. Therefore, you should limit your use of the login nodes to basic operations, and do not attempt to run anything in parallel on these nodes. | INCLINE has 26 25 compute nodes (c004 is disabled). Each compute node has two AMD EPYC 7662 CPUS, for a total of 128 cores. Hyperthreading can allow up to 256 effective threads, although only 128 MPI tasks are currently allowed. Each compute node has 256GB of memory. Most users will want to use compute nodes, unless their codes are specifically designed for GPUs or have special memory requirements. | INCLINE has two high memory nodes. These are identical to the compute nodes except that they have 2048 GB of memory. You should use high memory nodes only if you specifically require high memory applications. Please note that high memory is not equivalent to "big data", which may work with large quantities of data but may keep the majority of the data on disk. That is, you should plan to use high memory nodes if your application requires a great deal of RAM. | INCLINE has two GPU nodes. Each GPU node has two AMD 7452 CPUs, for a total of 64 cores (128 threads), and 1024 GB of RAM. Each GPU node also has two NVIDIA A100 GPUs. You should only plan to use the GPU nodes if your code is specifically designed for GPU hardware. Many deep learning codes (TensorFlow) have been designed for GPUs. It is recommended that you test your code on a separate GPU platform before attempting to run on incline. |
...