Cambricon-F
Yongwei Zhao, Zidong Du, Qi Guo, Shaoli Liu, Ling Li, Zhiwei Xu, Tianshi Chen, Yunji Chen · 2019
Machine learning techniques are pervasive tools for emerging commercial applications and many dedicated machine learning computers on different scales have been deployed in embedded devices, servers, and data centers. Currently, most machine learning computer architectures still focus on optimizing performance and energy efficiency instead of programming productivity. However, with the fast development in silicon technology, programming productivity, including programming itself and software stack development, becomes the vital reason instead of performance and power efficiency that hinders the application of machine learning computers.