Data Processing Apparatus Vector Computation Discrete Data Overhead
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Solution Overview
Problem
Current data processing technologies for artificial intelligence, particularly in image recognition, face complexity and high data overhead due to the cumbersome processing of discrete data points.
Innovation Solution
A data processing apparatus comprising a decoding unit, discrete-address determining unit, continuous-data caching unit, and data read/write unit, which decodes processing instructions, determines storage addresses for discrete and continuous data, and caches data to simplify vector computations by transferring discrete data to continuous addresses or storing continuous data to discrete addresses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If discrete data points are processed using traditional technologies, then processing accuracy can be maintained, but the processing process becomes complicated and data overhead increases
Solution Approach 1:
The patent changes the data representation parameter from discrete address-based storage to continuous address-based storage. By transforming discrete data points into continuous data structures with associated address information, the system maintains processing accuracy while simplifying the data processing workflow and reducing complexity in data handling operations.
Solution Approach 2:
The patent introduces an intermediary data structure that bridges discrete data points and continuous processing. This intermediary structure includes continuous data elements paired with address information, which mediates between the discrete nature of input data and the continuous processing requirements, thereby reducing processing complexity while maintaining accuracy.
2Measurement precision
If discrete data points are processed using traditional technologies, then data can be handled accurately, but data overhead becomes high
Solution Approach 1:
The patent changes the data storage parameter from discrete to continuous address space. By representing data through continuous addresses rather than discrete indices, the system reduces the metadata overhead associated with tracking individual data points while maintaining the precision needed for accurate processing.
Solution Approach 2:
The patent merges the data value with its address information into a unified continuous data structure. This combination eliminates the need for separate discrete data structures and their associated overhead, reducing data overhead while preserving measurement precision through the integrated address-value representation.
3Productivity
If vector computation is implemented to simplify processing, then processing efficiency improves, but data transformation complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing the continuous data structure and address mapping before actual computation. By preparing the data in advance in the continuous address format, the system enables efficient vector computation without introducing complexity during the computation process itself, as the data transformation is completed beforehand.
Data Source
AI summary
The present disclosure relates to a data processing apparatus and related products. The data processing apparatus includes a decoding unit, a discrete-address determining unit, a continuous-data caching unit, a data read/write unit, and a storage unit. Through the data processing apparatus, the processing instruction may be decoded and executed. Discrete data may be transferred to a continuous data address, or continuous data may be stored to multiple discrete data addresses. As such, a vector computation of discrete data and vector data restoration after the vector computation may be implemented, which may simplify a processing process, thereby reducing data overhead.