17664905. COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
- 1 COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Original Abstract Submitted
COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME
Organization Name
Inventor(s)
Sanghwa Jin of Seongnam-si (KR)
COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 17664905 titled 'COMPUTATIONAL STORAGE DEVICE FOR DEEP-LEARNING RECOMMENDATION SYSTEM AND METHOD OF OPERATING THE SAME
Simplified Explanation
The abstract describes a computational storage device for a deep-learning recommendation system (DLRS) that includes a nonvolatile memory and a storage controller. The storage controller controls the operation of the nonvolatile memory, stores off-loaded applications from a host device, and supports the execution of the DLRS by performing calculations based on embedding tables.
- The computational storage device includes a nonvolatile memory and a storage controller.
- The nonvolatile memory stores embedding tables for a deep-learning recommendation system (DLRS).
- The storage controller controls the operation of the nonvolatile memory.
- The storage controller stores off-loaded applications from a host device executing the DLRS.
- The storage controller supports the execution of the DLRS by executing the applications and performing calculations based on the embedding tables.
- The storage controller includes a machine learning engine.
- The machine learning engine analyzes the embedding tables and applications to determine a management scheme.
Potential Applications
- Deep-learning recommendation systems (DLRS)
- Computational storage devices for DLRS
- Off-loading applications from host devices
Problems Solved
- Efficient storage and execution of embedding tables for DLRS
- Off-loading applications from host devices to improve performance
- Determining an optimal management scheme for embedding tables and applications
Benefits
- Improved performance and efficiency of DLRS
- Reduced load on host devices
- Enhanced storage and execution capabilities for DLRS
Original Abstract Submitted
A computational storage device includes a nonvolatile memory configured to store a plurality of embedding tables for a deep-learning recommendation system (DLRS), and a storage controller configured to control an operation of the nonvolatile memory, store a plurality of applications that are off-loaded from a host device executing the DLRS, and support an execution of the DLRS by executing the plurality of applications and performing a plurality of calculations based on the plurality of embedding tables. The storage controller includes a machine learning engine configured to determine a management scheme of at least one embedding table of the plurality of embedding tables and the plurality of applications by analyzing the at least one embedding table and the plurality of applications.
