Arithmetic Formats for Machine Learning

In the field of machine learning, there is increasing interest in and deployment of low-bit-width floating point formats. These formats, typically eight-bit, but increasingly even smaller, have proved valuable in reducing computational requirements while maintaining accuracy and utility of the machine learning algorithms on which our society increasingly depends for security, medicine, and numerous industrial applications in agriculture, entertainment, transport, and many others. The aim of WG P3109 is to synthesize existing practice and to define a set of arithmetic formats which best serve this growing community of practice. This talk will represent the discussions and key ideas and rationales behind the working group's current decisions, as represented in the interim report of September 2023.

talks/p3109.txt ยท Last modified: 2024/06/21 11:11 by awf
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