FPGA Based Deep Learning Accelerators Take on ASICs
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 - Embedded Computing Design
An on-chip photonic deep neural network for image classification | Nature
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Deep Neural Network ASICs The Ultimate Step-By-Step Guide eBook : Blokdyk, Gerardus: Amazon.in: Kindle Store
Intel Speeds AI Development, Deployment and Performance with New Class of AI Hardware from Cloud to Edge | Business Wire
Why ASICs Are Becoming So Widely Popular For AI
Processing AI at the Edge: GPU, VPU, FPGA, ASIC Explained - ADLINK Blog
My take on the Gartner Hype Cycle | by Jens Møllerhøj | Medium
Deep Learning in Mining Biological Data | SpringerLink
Are ASIC Chips The Future of AI?
Embedded deep learning creates new possibilities across disparate industries | Vision Systems Design
The Great Debate of AI Architecture | Engineering.com
FPGA vs GPU for Machine Learning Applications: Which one is better? - Blog - Company - Aldec
Analog architectures for neural network acceleration based on non-volatile memory: Applied Physics Reviews: Vol 7, No 3
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Are ASIC Chips The Future of AI?
Deep Learning Accelerators Foundation IP| DesignWare IP| Synopsys
Deep learning on mobile devices: a review
ASIC Design Services | Microsemi
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
8-Bit Precision for Training Deep Learning Systems | IBM Research Blog
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
