18312817. COMPUTATIONAL STORAGE DEVICE, STORAGE SYSTEM INCLUDING THE SAME AND OPERATION METHOD THEREFOR simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
COMPUTATIONAL STORAGE DEVICE, STORAGE SYSTEM INCLUDING THE SAME AND OPERATION METHOD THEREFOR
Organization Name
Inventor(s)
COMPUTATIONAL STORAGE DEVICE, STORAGE SYSTEM INCLUDING THE SAME AND OPERATION METHOD THEREFOR - A simplified explanation of the abstract
This abstract first appeared for US patent application 18312817 titled 'COMPUTATIONAL STORAGE DEVICE, STORAGE SYSTEM INCLUDING THE SAME AND OPERATION METHOD THEREFOR
Simplified Explanation
The patent application describes a computational storage device that includes a control module and a nonvolatile memory. The nonvolatile memory stores a plurality of graph data elements, which consist of nodes and edges that connect the nodes. The memory is divided into two areas with different read speeds. The control module stores a graph data element with a high degree of association with one node in the first memory area, and a graph data element with a low degree of association with the same node in the second memory area.
- The computational storage device includes a control module and a nonvolatile memory.
- The nonvolatile memory stores graph data elements consisting of nodes and edges.
- The memory is divided into two areas with different read speeds.
- The control module stores graph data elements with different degrees of association with a specific node in the two memory areas.
Potential Applications:
- Big data analytics: The computational storage device can efficiently store and retrieve graph data, enabling faster processing and analysis of large datasets.
- Machine learning: The device can be used to store and access graph-based models, improving the performance of machine learning algorithms that rely on graph data.
- Network optimization: The device can store network graphs and optimize routing algorithms, leading to improved network performance and efficiency.
Problems Solved:
- Storage efficiency: The use of different memory areas with varying read speeds allows for the storage of graph data elements based on their degree of association, optimizing storage space and retrieval speed.
- Data processing speed: By storing graph data elements with high association in a faster memory area, the device can quickly access and process critical information, improving overall system performance.
Benefits:
- Improved performance: The computational storage device enhances data processing speed and efficiency by storing graph data elements in different memory areas based on their association with specific nodes.
- Space optimization: The device optimizes storage space by allocating memory areas with different read speeds, ensuring that frequently accessed data is stored in faster memory.
- Enhanced data analysis: The ability to efficiently store and retrieve graph data enables faster and more accurate analysis, benefiting applications such as big data analytics and machine learning.
Original Abstract Submitted
A computational storage device includes a control module, and a nonvolatile memory connected to the control module. The nonvolatile memory is configured to store a plurality of graph data elements, which comprises a plurality of nodes and a plurality of edges that connect at least a portion of the plurality of nodes to each other, in a first memory area and a second memory area each having a plurality of blocks and having different read speeds. The control module is configured to store a first graph data element of the plurality of graph data elements having a relatively high degree of association with one node of the plurality of nodes in the first memory area, and store a second graph data element of the plurality of graph data elements having a relatively low degree of association with the one node of the plurality of nodes in the second memory area.
