| ACCESS HPC Workshop Series |
Learning |
deep-learning, machine-learning, neural-networks, big-data, tensorflow, gpu, training, openmpi, c, c++, fortran, openmp, programming, mpi, spark |
|
| ACCESS KB Guide - Expanse |
Docs |
expanse, composable-systems, gpu |
|
| ACES: Charliecloud Containers for Scientific Workflows (Tutorial) |
Learning |
ACES, TAMU, scratch, lammps, tensorflow, open-ondemand, gpu, nfs, slurm, bash, training, python, containers |
|
| AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure |
Docs |
ACES, documentation, TAMU, ai, visualization, deep-learning, machine-learning, neural-networks, login, authentication, composable-systems, gpu, nvidia, slurm, bash, modules, vim, anaconda, conda, programming, python, scikit-learn |
|
| DELTA Introductory Video |
video |
delta, gpu, training |
|
| Examples of Thrust code for GPU Parallelization |
Learning |
parallelization, gpu, cuda |
|
| GPU Acceleration in Python |
Learning |
machine-learning, big-data, data-analysis, optimization, parallelization, gpu, cuda, python |
|
| GPU Computing Workshop Series for the Earth Science Community |
Learning |
optimization, performance-tuning, profiling, parallelization, github, pytorch, tensorflow, oceanography, gpu, hpc-arch-and-perf, training, c, c++, fortran, cuda, jupyterhub, programming, programming-best-practices, python |
|
| Horovod: Distributed deep learning training framework |
Tool |
deep-learning, distributed-computing, gpu |
|
| Introduction to Deep Learning in Pytorch |
Learning |
ai, deep-learning, image-processing, machine-learning, neural-networks, pytorch, gpu |
|
| Introduction to GPU/Parallel Programming using OpenACC |
Slides |
gpu, c, c++, compiling, fortran |
|
| Introduction to Parallel Programming for GPUs with CUDA |
Learning |
gpu, nvidia, c, c++, cuda |
|
| Thrust resources |
Learning |
parallelization, gpu, resources |
|