Invention Application
- Patent Title: INSTRUCTIONS AND LOGIC TO PERFORM FLOATING POINT AND INTEGER OPERATIONS FOR MACHINE LEARNING
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Application No.: US17834482Application Date: 2022-06-07
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Publication No.: US20220357945A1Publication Date: 2022-11-10
- Inventor: Himanshu Kaul , Mark A. Anders , Sanu K. Mathew , Anbang Yao , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Tatiana Shpeisman , Abhishek R. Appu , Altug Koker , Kamal Sinha , Balaji Vembu , Nicolas C. Galoppo Von Borries , Eriko Nurvitadhi , Rajkishore Barik , Tsung-Han Lin , Vasanth Ranganathan , Sanjeev Jahagirdar
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Main IPC: G06F9/30
- IPC: G06F9/30 ; G09G5/393 ; G06F9/38 ; G06F7/483 ; G06F7/544 ; G06N3/04 ; G06N3/063 ; G06N3/08

Abstract:
One embodiment provides a graphics processor comprising a memory controller and a graphics processing resource coupled with the memory controller. The graphics processing resource includes circuitry configured to execute an instruction to perform a matrix operation on first input including weight data and second input including input activation data, generate intermediate data based on a result of the matrix operation, quantize the intermediate data to a floating-point format determined based on a statistical distribution of first output data, and output, as second output data, quantized intermediate data in a determined floating-point format.
Public/Granted literature
- US11720355B2 Instructions and logic to perform floating point and integer operations for machine learning Public/Granted day:2023-08-08
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