insideHPC

Scalable and Distributed DNN Training on Modern HPC Systems

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 ...
TechNode

Briefing: Chinese researchers propose new, more efficient DNN training method

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook 51001614 - robotic hand, accessing on laptop, the virtual world of information. concept of ...
EurekAlert!

Early Bird uses 10 times less energy to train deep neural networks

HOUSTON -- (May 18, 2020) -- Rice University's Early Bird could care less about the worm; it's looking for megatons of greenhouse gas emissions. Early Bird is an energy-efficient method for training ...
Visual Studio Magazine

DNN Image Classification Using Keras

An example of an image classification problem is to identify a photograph of an animal as a "dog" or "cat" or "monkey." The two most common approaches for image classification are to use a standard ...
Semiconductor Engineering

Low-Power Heterogeneous Compute Cluster For TinyML DNN Inference And On-Chip Training

A new technical paper titled “DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training” was published by researchers at University of Bologna and ETH Zurich ...
InfoQ

Xipeng Shen on a New Technique to Reduce Deep-Learning Training Time

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
insideHPC

How to Achieve High-Performance, Scalable and Distributed DNN Training on Modern HPC Systems

In this video from the Stanford HPC Conference, DK Panda from Ohio State University presents: How to Achieve High-Performance, Scalable and Distributed DNN Training on Modern HPC Systems. This talk ...
Science Daily

Early Bird uses 10 times less energy to train deep neural networks

"This means you can train a DNN to achieve the same or even better accuracy for a given task in about 10% or less of the time needed for traditional training, which can lead to more than one order ...