Image Processing Apparatus Dependency Management
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Solution Overview
Problem
Conventional image processing apparatuses in multi-core systems face inefficiencies in processing due to pre-allocated processor tasks and dependency relationships between image processing tasks, which hinder the effective utilization of parallelism among processors.
Innovation Solution
An image processing apparatus and method that produces and utilizes dependent information to determine practicable image processing commands, allowing processors to perform tasks based on dependency relationships, enabling efficient parallel processing by writing only practicable commands to memory and managing performance completion information across image data blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If processing contents are previously allocated to multiple processors using pipeline processing, then processing efficiency is enhanced in conventional systems, but processing efficiency is lowered when processing methods diversify
Solution Approach 1:
The system dynamically determines processing assignments based on dependency relationships between image data blocks rather than using static pre-allocation. The determination unit identifies which blocks can be processed in parallel by analyzing dependencies, allowing the system to adapt processing assignments to the actual data characteristics and dependency structures, thereby maintaining high efficiency across diverse processing methods
Solution Approach 2:
The system segments image data into multiple blocks and processes them independently where possible. By dividing the image data and processing each block separately based on its dependency relationships, the system enables parallel processing of independent blocks while adapting to diverse processing requirements for different segments
2Productivity
If processors selectively perform processing to segments in the order registered in a process queue, then parallelism is improved compared to pipeline processing, but parallelism cannot be efficiently utilized when dependency relationships exist
Solution Approach 1:
The determination unit continuously analyzes dependency relationships between image data blocks and uses this feedback to dynamically adjust processing assignments. By monitoring which blocks have completed processing and which dependencies are satisfied, the system can immediately assign new blocks to become available processors, maximizing parallelism while correctly handling dependency constraints
Solution Approach 2:
The system performs preliminary analysis of dependency relationships between image data blocks before execution. By pre-identifying which blocks can be processed in parallel and which must wait for dependencies, the system prepares processing assignments in advance, enabling processors to immediately begin work on independent blocks without waiting for queue order
Data Source
AI summary
An image processing apparatus has a memory in which a plurality of image processing commands are stored, a dependent information producing unit which produces dependent information in each image data block becoming a target image processing, the dependent information indicating a dependency relationship between image processing of the image data block and another processing, a dependency relationship solving unit which makes a determination of a practicable image processing based on the dependent information, the dependency relationship solving unit writing an image processing command of the practicable image processing in the memory, and a plurality of image processing units which read an image processing command stored in the memory, the image processing units performing the image processing to the image data block based on the image processing command.