In this video from FOSDEM 2020, Frank McQuillan from Pivotal presents: Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases. In this session we will present an ...

Brain-inspired Spiking Neural Networks (SNN) and the parallel hardware necessary to exploit their full potential have promising features for robotic application. Besides the most obvious platform for ...

Over the last few years the idea of “conditional computation” has been key to making neural network processing more efficient, even though much of the hardware ecosystem has focused on general purpose ...

Supported neural networks will include MobileNetV2, ResNet-50 and VGG16. In addition, the new SDK release will include a TVM-based scheduler for automatically compiling and deploying AI models.

All-optical neural network for deep learning New approach could enable parallel computation with light Date: August 29, 2019 Source: The Optical Society Summary: In a key step toward making large ...

Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various ...

Optalysys optical processing powers convolutional neural network 04 Apr 2018 Breakthrough paves the way for deep learning applications, as company prepares to launch co-processor product.

Posted in Software Development, Software Hacks Tagged ai, artificial intellegence, gpu, neural net, neural network, parallel computing, parallel processing, tensorflow, WebGL ...