Google open-sourced the TensorFlow Runtime (TFRT), a new abstraction layer for their TensorFlow deep-learning framework that allows models to achieve better inference performance across different hard ...

Eager execution means that TensorFlow code runs when it is defined, as opposed to adding nodes and edges to a graph to be run in a session later, which was TensorFlow’s original mode.

New edge-inference machine-learning architectures have been arriving at an ... You’ll see terms like “sea-of-MACs,” “systolic array,” “dataflow architecture,” “graph processor,” and “streaming ...

Google today launched an OpenCL-based mobile GPU inference engine for its TensorFlow framework on Android. It’s available now in the latest version of the TensorFlow Lite library, and the ...

There is more info on the ML suite of tools Xilinx has developed for users, but in essence, this is an API that allows connectivity to the frameworks and makes it easier to get a trained model and ...

Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph structured data using TensorFlow, its machine learning framework.

Google has revealed new benchmark results for its custom TensorFlow processing unit, or TPU. In inference workloads, the company's ASIC positively smokes hardware from Intel, Nvidia.

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...