Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Hardware Acceleration of Deep Neural Network Models on FPGA ( Part 1 of 2) | ignitarium.com
Leveraging FPGAs for deep learning - Embedded.com
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Scaling for edge inference of deep neural networks | Nature Electronics
PDF) Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs
Deep Learning in Mining Biological Data | SpringerLink
FPGA Based Deep Learning Accelerators Take on ASICs
Hardware for Deep Learning Inference: How to Choose the Best One for Your Scenario - Deci
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
8-Bit Precision for Training Deep Learning Systems | IBM Research Blog
Project Detail | Efabless
How to Develop High-Performance Deep Neural Network Object Detection/Recognition Applications for FPGA-based Edge Devices - Embedded Computing Design
An on-chip photonic deep neural network for image classification | Nature
FPGA Based Deep Learning Accelerators Take on ASICs
The New Deep Learning Memory Architectures You Should Know About — eSilicon Technical Article | ChipEstimate.com
A Breakthrough in FPGA-Based Deep Learning Inference - EEWeb
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Future Internet | Free Full-Text | An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks
When not to use Neural Networks. Okay folks, so we all know the deal… | by Rahul Bhatia | DataDrivenInvestor
