Abstract: Cellular automata have ideal properties for scalable and efficient computing, but a lack of a training method limits their real-world applications. First, we propose to partition the ...

Hybrid cloud data management firm Cloudian Inc. today announced the availability of its new PyTorch connector with Remote Direct Memory Access support that delivers erformance improvements for ...

The mnist_entropy.py is the python training workload we will distribute to demonstrate the distribution. In the end we have a entrypoint which we overwrite when we execute it through training operator ...

NumberRecognition is a project aimed at recognizing handwritten digits from the MNIST dataset using PyTorch. It includes scripts for training and inference, along with utilities for dataset ...

Abstract: Neuromorphic and in-memory computing architectures using emerging nonvolatile memories (e-NVMs) have emerged as promising solutions for area- and energy-efficient deep neural network (DNN) ...