PyTorch, the Python framework for quick-and-easy creation of deep learning models, is now out in version 1.5. PyTorch 1.5 brings a major update to PyTorch’s C++ front end, the C++ interface to ...

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

Cloudian’s new PyTorch connector is built on Nvidia Corp.’s GPUDirect Storage technology and optimized for Nvidia Spectrum-X ...

“Blue Waters currently supports TensorFlow 1.3, PyTorch 0.3.0 and we hope to support CNTK and Horovod in the near future. This tutorial will go over the minimum ingredients needed to do distributed ...

Soumith Chintala, PyTorch project lead, seems to share Zaharia's ideas about distributed training being the next big thing in deep learning, as it has been introduced in the latest version of PyTorch.

The Data Science Lab. Generating Synthetic Data Using a Variational Autoencoder with PyTorch. Generating synthetic data is useful when you have imbalanced training data for a particular class, for ...

In this video from the Swiss HPC Conference, DK Panda from Ohio State University presents: Scalable and Distributed DNN Training on Modern HPC Systems. The current wave of advances in Deep Learning ...

Parallel tensors work with the graph fusion and kernel optimizations to help accelerate inference. PyTorch 2.1 is coming Ganti emphasized that IBM’s efforts to accelerate PyTorch for inferencing ...

On top of PyTorch, theator is also leveraging a machine-learning platform called Allegro Trains, which manages the data that comes in through the different models' pipelines and organizes them in ...