Self-regulating power management for a neural network system
A neural network runs a known input data set using an error free power setting and using an error prone power setting. The differences in the outputs of the neural network using the two different power settings determine a high level error rate associated with the output of the neural network using the error prone power setting. If the high level error rate is excessive, the error prone power setting is adjusted to reduce errors by changing voltage and/or clock frequency utilized by the neural network system. If the high level error rate is within bounds, the error prone power setting can remain allowing the neural network to operate with an acceptable error tolerance and improved efficiency. The error tolerance can be specified by the neural network application.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Advanced Micro Devices, Inc., Santa Clara, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC52-07NA27344
- Assignee:
- Advanced Micro Devices, Inc. (Santa Clara, CA)
- Patent Number(s):
- 11,294,747
- Application Number:
- 15/884,638
- OSTI ID:
- 1892798
- Country of Publication:
- United States
- Language:
- English
Similar Records
Opening up the black box of artificial neural networks
Adaptive neural network management system