Samsung electronics co., ltd. (20240202527). METHOD AND APPARATUS WITH NEURAL NETWORK OPTIMIZATION simplified abstract
Contents
METHOD AND APPARATUS WITH NEURAL NETWORK OPTIMIZATION
Organization Name
Inventor(s)
Seok-Young Yoon of Suwon-si (KR)
Jaume Mateu Cuadrat of Seoul (KR)
METHOD AND APPARATUS WITH NEURAL NETWORK OPTIMIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202527 titled 'METHOD AND APPARATUS WITH NEURAL NETWORK OPTIMIZATION
The abstract describes a method of processing data using a computing device to convert a neural network from one format to another, optimize the network based on hardware information, and partition it for efficient operation.
- Converting a neural network from one format to another
- Obtaining information about hardware for neural network operations
- Dividing the network into partitions based on hardware and partition information
- Optimizing each partition based on input-output relationships
- Converting the optimized partitions back to the original format
Potential Applications: - This technology can be used in various industries such as healthcare, finance, and autonomous vehicles for efficient data processing. - It can improve the performance of neural networks in tasks such as image recognition, natural language processing, and predictive analytics.
Problems Solved: - Addresses the need for optimizing neural networks for specific hardware configurations. - Improves the efficiency and speed of neural network operations.
Benefits: - Enhanced performance of neural networks on specialized hardware. - Increased accuracy and speed of data processing tasks. - Cost-effective solution for optimizing neural networks.
Commercial Applications: Title: "Optimized Neural Network Processing for Enhanced Performance" This technology can be applied in industries such as: - Healthcare for medical image analysis - Finance for fraud detection and risk assessment - Autonomous vehicles for real-time decision making
Questions about Optimized Neural Network Processing: 1. How does this technology improve the efficiency of neural network operations? - The technology optimizes neural networks based on hardware configurations, leading to faster and more accurate data processing.
2. What are the potential implications of using this technology in autonomous vehicles? - Implementing this technology in autonomous vehicles can improve real-time decision-making capabilities, enhancing safety and performance.
Original Abstract Submitted
a method of processing data is performed by a computing device including processing hardware and storage hardware, the method including: converting, by the processing hardware, a neural network, stored in the storage hardware, from a first neural network format into a second neural network format; obtaining, by the processing hardware, information about hardware configured to perform a neural network operation for the neural network and obtaining partition information; dividing the neural network in the second neural network format into partitions, wherein the dividing is based on the information about the hardware and the partition information, wherein each partition includes a respective layer with an input thereto and an output thereof; optimizing each of the partitions based on a relationship between the input and the output of the corresponding layer; and converting the optimized partitions into the first neural network format.
