18345492. METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT simplified abstract (Samsung Electronics Co., Ltd.)
Contents
- 1 METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Commercial Applications
- 1.9 Questions about Memory Optimization Technology for Deep Learning Systems
- 1.10 Original Abstract Submitted
METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT
Organization Name
Inventor(s)
METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18345492 titled 'METHOD AND APPARATUS WITH UNIFIED VIRTUAL MEMORY MANAGMENT
Simplified Explanation
The method involves updating memory allocation information in a UVM based on block information of model data blocks used for executing a deep learning model by a deep learning framework. It also includes performing a least recently used (LRU) eviction based on the updated memory allocation information.
- The method updates memory allocation information in a UVM based on block information of model data blocks.
- It performs a least recently used (LRU) eviction based on the updated memory allocation information.
- The innovation is focused on optimizing memory usage in deep learning models.
Potential Applications
This technology can be applied in various deep learning frameworks and systems where memory optimization is crucial. It can enhance the efficiency and performance of deep learning models by managing memory allocation effectively.
Problems Solved
The technology addresses the issue of inefficient memory usage in deep learning models, which can lead to performance bottlenecks and reduced overall efficiency. By implementing a method to update memory allocation information and perform LRU eviction, the technology aims to improve memory management in deep learning systems.
Benefits
- Improved memory usage efficiency in deep learning models - Enhanced performance and speed of deep learning frameworks - Optimal utilization of memory resources for better overall system efficiency
Commercial Applications
Title: Memory Optimization Technology for Deep Learning Systems This technology can be utilized in various industries such as healthcare, finance, and autonomous vehicles where deep learning models are extensively used. It can benefit companies developing AI solutions by improving the performance and efficiency of their systems.
Questions about Memory Optimization Technology for Deep Learning Systems
Question 1
How does the method update memory allocation information in a UVM based on block information of model data blocks?
The method updates memory allocation information by analyzing the block information of model data blocks used for executing a deep learning model and adjusting the memory allocation accordingly.
Question 2
What is the significance of performing a least recently used (LRU) eviction based on the updated memory allocation information?
Performing LRU eviction helps in removing the least recently used data blocks from memory, optimizing memory usage and improving the overall efficiency of the deep learning model.
Original Abstract Submitted
A method including updating memory allocation information of a UVM based on block information of model data blocks used for an execution of a deep learning model by a deep learning framework, and performing a least recently used (LRU) eviction based on the updated memory allocation information.
