These are the public key fingerprints for Cardinal:
cardinal: ssh_host_rsa_key.pub = 73:f2:07:6c:76:b4:68:49:86:ed:ef:a3:55:90:58:1b
cardinal: ssh_host_ed25519_key.pub = 93:76:68:f0:be:f1:4a:89:30:e2:86:27:1e:64:9c:09
cardinal: ssh_host_ecdsa_key.pub = e0:83:14:8f:d4:c3:c5:6c:c6:b6:0a:f7:df:bc:e9:2e
sbatch (instead of qsub) command to submit jobs. Refer to the Slurm migration page to understand how to use Slurm. It is strongly suggested to consider the memory use to the available per-core memory when users request OSC resources for their jobs.
MVAPICH is a standard library for performing parallel processing using a distributed-memory model.
AutoDock is a a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. AutoDock has applications in X-ray crystallography, structure-based drug design, lead optimization, etc.
Nodejs is used to create server-side web applications, and it is perfect for data-intensive applications since it uses an asynchronous, event-driven model
We can improve performace of python calculation by running python in parallel. In this turtorial we will be making use of the multithreading library to run python code in parallel.
If you plan on using GPUs in tensorflow or pytorch see HOWTO: Use GPU with Tensorflow and PyTorch
This is an exmaple to utilize a GPU to improve performace in our python computations. We will make use of the Numba python library. Numba provides numerious tools to improve perfromace of your python code including GPU support.
