CUDA is a parallel computing platform and programming model developed by NVIDIA for general purpose computing on GPU devices. CUDA application can dramatically sp...
By using the checkpoint feature, model progress can be saved during training. The model can resume training where it left off and avoid starting from scratch if s...
TensorFlow CPU Version First, grab a compute node with srun and start a Python Virtualenv environment: abc123@login 0 0 ~ $ srun n 80 N 1 time=48:00:00 pty b...
Parallelize Deep Learning Models Across Multiple GPU Devices Deep Learning models written in Tensorflow can automatically take advantage of a GPU device on a comp...
Frequently Asked Questions Who can use Shamu? The Shamu research cluster is available at no charge to all University of Texas at San Antonio students, faculty an...
Sample GPU submit script using the Caffe training network Using the Tesla K80 cards: #SBATCH partition="gpu" #SBATCH nodes=1 #SBATCH gres=gpu:k80:1 . /etc/prof...
Getting Help Shamu Office Hours Shamu Office hours are held in the Tech Cafe Monday through Friday 8am to 5pm. No appointment necessary, just drop by. Email UTS...
MXnet Apache MXNet is a modern open source deep learning framework used to train, and deploy deep neural networks. It is scalable, allowing for fast model trainin...
We have the GPU version of TensorFlow installed on the GPU nodes with the Python 3.6.1 module install (native Python 2.7 version is currently not working). This d...
: Arc User Guide Arc is the primary High Performance Computing (HPC) system at The University of Texas at San Antonio (UTSA) that can be used for running data in...