[basics- Hardware for Machine Learning](http://www.cs.cornell.edu/courses/cs6787/2017fa/Lecture11.pdf)
## [Grigory Sapunov](https://moocaholic.medium.com/) series [Hardware for Deep Learning. Part 4: ASIC](https://blog.inten.to/hardware-for-deep-learning-part-4-asic-96a542fe6a81)
https://www.nextplatform.com/2020/07/15/the-elegance-and-limitations-of-precisely-engineered-accelerators/
2018 [A Full Hardware Guide to Deep Learning](https://timdettmers.com/2018/12/16/deep-learning-hardware-guide/)
https://www.electronicproducts.com/top-10-processors-for-ai-acceleration-at-the-endpoint/#
## [42 Years of Microprocessor Trend Data](https://www.karlrupp.net/2018/02/42-years-of-microprocessor-trend-data/), take a look[[microprocessor-trend-data]]
## 2020 [NANO-CHIPS 2030 - On-Chip AI for an Efficient Data-Driven World](https://link.springer.com/book/10.1007/978-3-030-18338-7)
[The Memory Challenge in Ultra-Low Power Deep Learning](https://link.springer.com/chapter/10.1007/978-3-030-18338-7_19) Francesco Conti
## https://jonathan-hui.medium.com/ai-chips-technology-trends-landscape-mobile-soc-intel-asian-ai-chips-low-power-inference-4db701dbe85d