Invention Grant
- Patent Title: Training with adaptive runtime and precision profiling
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Application No.: US15581031Application Date: 2017-04-28
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Publication No.: US11017291B2Publication Date: 2021-05-25
- Inventor: Brian T. Lewis , Rajkishore Barik , Murali Sundaresan , Leonard Truong , Feng Chen , Xiaoming Chen , Mike B. Macpherson
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Jaffery Watson Mendonsa & Hamilton LLP
- Main IPC: G06N3/00
- IPC: G06N3/00 ; G06N3/063 ; G06N3/04 ; G06F7/483 ; G06N3/08

Abstract:
A mechanism is described for facilitating efficient training of neural networks at computing devices. A method of embodiments, as described herein, includes detecting one or more inputs for training of a neural network, and introducing randomness in floating point (FP) numbers to prevent overtraining of the neural network, where introducing randomness includes replacing less-significant low-order bits of operand and result values with new low-order bits during the training of the neural network.
Public/Granted literature
- US20180314935A1 TRAINING WITH ADAPTIVE RUNTIME AND PRECISION PROFILING Public/Granted day:2018-11-01
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N3/00 | 基于生物学模型的计算机系统 |