Hyundai motor company (20240095142). APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF simplified abstract
Contents
- 1 APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF
Organization Name
Inventor(s)
Jin Sol Kim of Hwaseong-si (KR)
APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095142 titled 'APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF
Simplified Explanation
The patent application describes an apparatus for processing a deep learning model that optimizes memory usage and processing time for each layer of the model.
- The controller in the apparatus detects memory usage, first processing time, and second processing time for each layer of the deep learning model.
- Based on an objective function, the controller determines the optimal memory for each layer of the deep learning model.
Potential Applications
This technology could be applied in various fields such as image recognition, natural language processing, and autonomous driving systems.
Problems Solved
1. Efficient memory usage in deep learning models. 2. Optimization of processing time for each layer of the model.
Benefits
1. Improved performance of deep learning models. 2. Reduction in memory overhead. 3. Faster processing times for deep learning tasks.
Potential Commercial Applications
Optimizing memory usage and processing time in deep learning models can benefit companies developing AI solutions for industries such as healthcare, finance, and e-commerce.
Possible Prior Art
Prior art in the field of deep learning model optimization includes research papers and patents related to memory management and performance optimization in neural networks.
Unanswered Questions
How does the apparatus handle different types of deep learning models?
The patent application does not specify if the apparatus is designed to work with specific types of deep learning models or if it is a general-purpose solution.
What impact does the optimization of memory usage have on energy consumption?
The patent application does not address the potential impact of memory optimization on the energy consumption of the processing system.
Original Abstract Submitted
an apparatus for processing a deep learning model includes a first memory, a second memory, and a controller. the controller is configured to, for each layer of the deep learning model, detect memory usage, a first processing time corresponding to the first memory being used, and a second processing time corresponding to the second memory being used, and determine an optimal memory for each layer of the deep learning model based on an objective function.
