Invention Application
- Patent Title: INSTRUCTIONS AND LOGIC TO PERFORM FLOATING POINT AND INTEGER OPERATIONS FOR MACHINE LEARNING
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Application No.: US17115989Application Date: 2020-12-09
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Publication No.: US20210124579A1Publication Date: 2021-04-29
- 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 for a graphics processing unit to accelerate machine-learning operations, the graphics processing unit comprising a multiprocessor having a single instruction, multiple thread (SIMT) architecture, the multiprocessor to execute at least one single instruction; and a first compute unit included within the multiprocessor, the at least one single instruction to cause the first compute unit to perform a two-dimensional matrix multiply and accumulate operation, wherein to perform the two-dimensional matrix multiply and accumulate operation includes to compute a 32-bit intermediate product of 16-bit operands and to compute a 32-bit sum based on the 32-bit intermediate product.
Public/Granted literature
- US12141578B2 Instructions and logic to perform floating point and integer operations for machine learning Public/Granted day:2024-11-12
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