Nvidia corporation (20240338358). CONCURRENT DATASET UPDATES USING HASH MAPS simplified abstract
Contents
CONCURRENT DATASET UPDATES USING HASH MAPS
Organization Name
Inventor(s)
Pascal Gautron of Speracedes (FR)
CONCURRENT DATASET UPDATES USING HASH MAPS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338358 titled 'CONCURRENT DATASET UPDATES USING HASH MAPS
Simplified Explanation: The patent application discusses approaches to update spatial hash maps while ensuring atomicity for arbitrary data structures, such as pixels in an image.
Key Features and Innovation:
- Spatial hash map updates with atomicity for arbitrary data structures.
- Aggregation of change requests for independent values corresponding to a hash map entry.
- Multi-resolution spatial hashing for propagating changes across different levels.
Potential Applications: This technology can be applied in rendering images, real-time graphics processing, spatial data processing, and multi-resolution data storage systems.
Problems Solved: This technology addresses the challenge of updating spatial hash maps with atomicity for complex data structures, ensuring consistency and reliability in data processing.
Benefits:
- Improved efficiency in updating spatial hash maps.
- Enhanced data consistency and reliability.
- Scalability for handling large datasets with multiple independent values.
Commercial Applications: Potential commercial applications include real-time rendering engines, geographic information systems, virtual reality applications, and database management systems.
Prior Art: Prior art related to this technology may include research on spatial data structures, concurrency control mechanisms, and multi-resolution data storage techniques.
Frequently Updated Research: Researchers may be exploring optimizations for multi-threaded spatial hash map updates, advancements in atomicity guarantees for complex data structures, and applications of spatial hashing in diverse fields.
Questions about Spatial Hash Map Updates: 1. How does this technology improve the efficiency of updating spatial hash maps for complex data structures? 2. What are the potential challenges in implementing multi-resolution spatial hashing for propagating changes across different levels?
Original Abstract Submitted
approaches in accordance with various embodiments can perform spatial hash map updates while ensuring the atomicity of the updates for arbitrary data structures. a hash map can be generated for a dataset where entries in the hash map may correspond to multiple independent values, such as pixels of an image to be rendered. update requests for independent values may be received on multiple concurrent threads, but change requests for independent values corresponding to a hash map entry can be aggregated from a buffer and processed iteratively in a single thread for a given hash map entry. in the case of multi-resolution spatial hashing where data can be stored at various discretization levels, this operation can be repeated to propagate changes from one level to another.
