Can You Close the Performance Gap Between GPU and CPU for Deep Learning Models? - Deci
Google Teaches AI To Play The Game Of Chip Design
Intel Throws Down AI Gauntlet With Neural Network Chips
Make Every feature Binary: A 135B parameter sparse neural network for massively improved search relevance - Microsoft Research
DeepMind, Oxford U, IDSIA, Mila & Purdue U's General Neural Algorithmic Learner Matches Task-Specific Expert Performance | Synced
An optical neural chip for implementing complex-valued neural network | Nature Communications
Frontiers | Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems
Scalable multi-node deep learning training using GPUs in the AWS Cloud | AWS Machine Learning Blog
Neural Magic's sparsity, Nvidia's Hopper, and Alibaba's network among firsts in latest MLPerf AI benchmarks | ZDNET
13.7. Parameter Servers — Dive into Deep Learning 1.0.0-beta0 documentation
Multi-GPU and Distributed Deep Learning - frankdenneman.nl
Production Deep Learning with NVIDIA GPU Inference Engine | NVIDIA Technical Blog
Binarized Neural Networks: An Overview | by Wilson Wang | Towards Data Science
Options for training deep learning neural network - MATLAB trainingOptions
Do we really need GPU for Deep Learning? - CPU vs GPU | by Shachi Shah | Medium
Chip Design with Deep Reinforcement Learning – Google AI Blog
Brian2GeNN: accelerating spiking neural network simulations with graphics hardware | Scientific Reports
PyTorch-Direct: Introducing Deep Learning Framework with GPU-Centric Data Access for Faster Large GNN Training | NVIDIA On-Demand
Training Feed Forward Neural Network(FFNN) on GPU — Beginners Guide | by Hargurjeet | MLearning.ai | Medium
CPU vs GPU in Machine Learning Algorithms: Which is Better?
A Quick Introduction to Neural Networks – Ujjwal Karn
Artificial neural network - Wikipedia
Neural network - Wikipedia
Hardware for Deep Learning Inference: How to Choose the Best One for Your Scenario - Deci
