Nodejs
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
Pitzer
Running jobs requeued on all clusters
The Slurm upgrades during rolling reboots of Ascend, Owens and Pitzer we performed today (Oct 25 2023) cause all running jobs on the systems requeued around 8:45am. You will not be billed for the consumed resources before the jobs were requeued.
Rolling reboot of all clusters starting from Oct 25 2023
We will have rolling reboots of Ascend, Owens and Pitzer clusters including login and compute nodes, starting from 9AM Wednesday October 25, to perform NVIDIA driver and Slurm upgrades. At the start of the rolling reboot all login nodes will be unavailable for about 10 minutes. The rolling reboots won't affect any running batch jobs, but users may experience longer queue wait time than usual on the clusters.
HOWTO: Use GPU with Tensorflow and PyTorch
GPU Usage on Tensorflow
Environment Setup
To begin, you need to first create and new conda environment or use an already existing one. See HOWTO: Create Python Environment for more details. In this example we are using python/3.6-conda5.2
Once you have a conda environment created and activated we will now install tensorflow-gpu into the environment (In this example we will be using version 2.4.1 of tensorflow-gpu:
conda install tensorflow-gpu=2.4.1
HOWTO: Run Python in Parallel
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.
HOWTO: Use GPU in Python
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.
