The Deep Learning Inference Acceleration Blog Series — Part 2- Hardware | by Amnon Geifman | Towards Data Science
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Space-efficient optical computing with an integrated chip diffractive neural network | Nature Communications
Power and throughput among CPU, GPU, FPGA, and ASIC. | Download Scientific Diagram
Intel's DLA: Neural Network Inference Accelerator [200]. | Download Scientific Diagram
Applied Sciences | Free Full-Text | MLoF: Machine Learning Accelerators for the Low-Cost FPGA Platforms
FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review
The Great Debate of AI Architecture | Engineering.com
AI 2.0 - Episode #1, Introduction | Cisco Tech Blog
Review of ASIC accelerators for deep neural network - ScienceDirect
Understanding the Deployment of Deep Learning algorithms on Embedded Platforms
A Breakthrough in FPGA-Based Deep Learning Inference - EEWeb
Deep Learning
Embedded Hardware for Processing AI - ADLINK Blog
Frontiers | Always-On Sub-Microwatt Spiking Neural Network Based on Spike-Driven Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Blog: Aldec Blog - How to develop high-performance deep neural network object detection/recognition applications for FPGA-based edge devices - FirstEDA
Are ASIC Chips The Future of AI?
An on-chip photonic deep neural network for image classification | Nature
Hardware for Deep Learning Inference: How to Choose the Best One for Your Scenario - Deci
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Processing Units - CPU, GPU, APU, TPU, VPU, FPGA, QPU - PRIMO.ai
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Deep Neural Network ASICs The Ultimate Step-By-Step Guide by Gerardus Blokdyk - Ebook | Scribd
