18096650. APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF simplified abstract (KIA CORPORATION)
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 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 18096650 titled 'APPARATUS FOR PROCESSING A DEEP LEARNING MODEL AND A METHOD THEREOF
Simplified Explanation
The apparatus described in the patent application is designed to optimize memory usage and processing time for each layer of a deep learning model by determining the optimal memory for each layer based on an objective function. This is achieved by detecting memory usage, processing times for different memories, and making decisions to improve efficiency.
- The apparatus includes a first memory, a second memory, and a controller.
- The controller is responsible for detecting memory usage, processing times for each memory, and determining the optimal memory for each layer of the deep learning model.
- The optimization process is based on an objective function, which helps in making decisions to improve efficiency.
Potential Applications
This technology can be applied in various fields where deep learning models are used, such as image recognition, natural language processing, and autonomous vehicles.
Problems Solved
1. Optimizing memory usage and processing time in deep learning models. 2. Improving efficiency and performance of deep learning algorithms.
Benefits
1. Enhanced performance of deep learning models. 2. Reduced memory usage and processing time. 3. Improved accuracy and speed of computations.
Potential Commercial Applications
Optimizing memory usage and processing time in deep learning models can be beneficial for companies developing AI applications, autonomous systems, and other advanced technologies.
Possible Prior Art
Prior art in the field of deep learning optimization techniques may include research papers, patents, or products that focus on improving the efficiency of neural networks through memory optimization and processing time reduction.
What are the specific components of the apparatus described in the patent application?
The specific components of the apparatus include a first memory, a second memory, and a controller responsible for detecting memory usage, processing times for different memories, and determining the optimal memory for each layer of the deep learning model.
How does the controller determine the optimal memory for each layer of the deep learning model?
The controller determines the optimal memory for each layer based on an objective function, which takes into account factors such as memory usage, processing times for different memories, and efficiency improvements.
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.
