Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
An on-chip photonic deep neural network for image classification | Nature
FPGA vs GPU for Machine Learning Applications: Which one is better? - Blog - Company - Aldec
Intel Unveils FPGA to Accelerate Neural Networks
Analog architectures for neural network acceleration based on non-volatile memory: Applied Physics Reviews: Vol 7, No 3
Processing AI at the Edge: GPU, VPU, FPGA, ASIC Explained - ADLINK Blog
FPGA Based Deep Learning Accelerators Take on ASICs
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Embedded deep learning creates new possibilities across disparate industries | Vision Systems Design
Google AI Blog: Chip Design with Deep Reinforcement Learning
Deep Learning in Mining Biological Data | SpringerLink
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
My take on the Gartner Hype Cycle | by Jens Møllerhøj | Medium
How to Develop High-Performance Deep Neural Network Object Detection/Recognition Applications for FPGA-based Edge Devices - Embedded Computing Design
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Why ASICs Are Becoming So Widely Popular For AI
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
Embedded Machine Learning
Are ASIC Chips The Future of AI?
The Great Debate of AI Architecture | Engineering.com
8-Bit Precision for Training Deep Learning Systems | IBM Research Blog
Arch-Net: A Family Of Neural Networks Built With Operators To Bridge The Gap Between Computer Architecture of ASIC Chips And Neural Network Model Architectures - MarkTechPost
FPGA Based Deep Learning Accelerators Take on ASICs
