FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review
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Are ASIC Chips The Future of AI?
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
Deep Neural Network ASICs The Ultimate Step-By-Step Guide: Gerardus Blokdyk: 9780655403975: Textbooks: Amazon Canada
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
5 Emerging Technology Trends and 2018 Hype Cycle | Gartner
FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
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.
FPGA Based Deep Learning Accelerators Take on ASICs - The Next Platform
Hardware for Deep Learning Inference: How to Choose the Best One for Your Scenario - Deci
Are ASIC Chips The Future of AI?
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
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
Designing With ASICs for Machine Learning in Embedded Systems | NWES Blog
An on-chip photonic deep neural network for image classification | Nature
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.
FPGA Based Deep Learning Accelerators Take on ASICs - The Next Platform
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
AI 2.0 - Episode #1, Introduction | Cisco Tech Blog
Frontiers | Always-On Sub-Microwatt Spiking Neural Network Based on Spike-Driven Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
