Are ASIC Chips The Future of AI?
Understanding the Deployment of Deep Learning algorithms on Embedded Platforms
Deep Learning
Applied Sciences | Free Full-Text | MLoF: Machine Learning Accelerators for the Low-Cost FPGA Platforms
Review of ASIC accelerators for deep neural network - ScienceDirect
FPGA Based Deep Learning Accelerators Take on ASICs - The Next Platform
GitHub - coleblackman/TIDENet: TIDENet is an ASIC written in Verilog for Tiny Image Detection at Edge with neural networks (TIDENet) using DNNWeaver 2.0, the Google SkyWater PDK, OpenLANE, and Caravel.
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
An on-chip photonic deep neural network for image classification | Nature
Autonomous Vehicles Drive AI Chip Innovation - Edge AI and Vision Alliance
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Are ASIC Chips The Future of AI?
Webinar: ASICs Unlock Deep Learning Innovation - SemiWiki
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
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
Blog: Aldec Blog - How to develop high-performance deep neural network object detection/recognition applications for FPGA-based edge devices - FirstEDA
Deep Neural Network ASICs The Ultimate Step-By-Step Guide by Gerardus Blokdyk - Ebook | Scribd
Designing With ASICs for Machine Learning in Embedded Systems | NWES Blog
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
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
How to develop high-performance deep neural network object detection/recognition applications for FPGA-based edge devices - Blog - Company - Aldec
Eta's Ultra Low-Power Machine Learning Platform - EE Times
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
Embedded Hardware for Processing AI - ADLINK Blog
