This standard defines a binary arithmetic and data format for machine learning-optimized domains. It also specifies the default handling of exceptions occurring in this arithmetic. This standard provides a consistent and flexible arithmetic framework optimized for Machine Learning Systems (MLSs) in hardware and/or software implementations to minimize the work required to make MLSs interoperable with each other as well as other dependent systems. This standard is aligned with the IEEE Std 754-2019 Standard for Floating-Point Arithmetic.
- Standard Committee
- C/MSC - Microprocessor Standards Committee
- Joint Sponsors
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CASS/DSA-SC
- Status
- Active PAR
- PAR Approval
- 2023-02-15
Working Group Details
- Society
- IEEE Computer Society
- Standard Committee
- C/MSC - Microprocessor Standards Committee
- Working Group
-
AFM - Arithmetic Formats for Machine Learning
Learn More About AFM - Arithmetic Formats for Machine Learning - IEEE Program Manager
- Tom Thompson
Contact Tom Thompson - Working Group Chair
- Kiran Gunnam
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