Stream Processor Selection for Dynamic Load Balancing
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Solution Overview
Problem
Existing data processing systems with multiple stream processors face challenges in adaptively managing load balance, particularly when processing multimedia data with varying types and amounts, leading to inefficiencies and potential idle processors.
Innovation Solution
A data processing apparatus and method that includes a selection unit generating stream processor status information and assigning priorities based on processor core and internal memory statuses to select the most suitable stream processor for data input, allowing for dynamic load balancing and efficient data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a load balancing scheme uniformly allocates load to multiple stream processors, then data processing performance is enhanced, but the system cannot adaptively cope with varying data types and amounts over time
Solution Approach 1:
The patent implements dynamic load balancing by continuously monitoring stream processor status information and adjusting task allocation in real-time. The selection unit dynamically selects which stream processor to allocate new tasks to based on current status, transforming the static uniform allocation into an adaptive dynamic system that responds to changing data characteristics and processor states.
Solution Approach 2:
The system employs feedback mechanisms by monitoring stream processor status information (including processor core status and internal memory status) and using this feedback to make informed allocation decisions. The selection unit receives status feedback from multiple stream processors and uses this information to selectively allocate tasks, creating a closed-loop control system that adapts to varying conditions.
2Productivity
If stream processor status monitoring and selection is implemented, then optimal processor selection is achieved, but device complexity increases
Solution Approach 1:
Each stream processor autonomously generates and maintains its own status information regarding its processor core and internal memory states. This self-service approach allows processors to independently report their readiness status without requiring complex centralized monitoring infrastructure, reducing overall system complexity while enabling informed selection decisions.
Solution Approach 2:
The status monitoring function is segmented and distributed across individual stream processors rather than centralized in a single monitoring unit. Each processor independently tracks its own status (processor core status and internal memory status), dividing the monitoring complexity into manageable independent units that can be easily managed and scaled.
3Ease of operation
If priority assignment based on multiple status parameters is implemented, then optimal load distribution is achieved, but the selection process becomes more complex
Solution Approach 1:
The system uses parameter changes by varying the priority levels assigned to stream processors based on their status parameters (processor core status and internal memory status). Different status combinations result in different priority assignments, allowing the system to adaptively adjust load distribution by changing the selection criteria parameters rather than implementing complex decision logic.
Data Source
AI summary
Provided are a data processing apparatus and a method of controlling the data processing apparatus. The data processing apparatus may select a single stream processor from a plurality of stream processors based on stream processor status information, and input data into the selected stream processor. The stream processor status information may include first status information of a processor core and second status information of at least one internal memory.