Task Queue Checkpoints for Dynamic Execution State Monitoring
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Solution Overview
Problem
Conventional processor chips face difficulties in dynamically monitoring and scheduling task execution states, leading to inefficiencies in task management.
Innovation Solution
A data redundancy method that divides data into importance ranks, extracts critical bits, and applies redundancy processing techniques such as replica redundancy and error correcting codes to ensure data consistency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If common launching mode is used to execute tasks, then task execution is simple to implement, but dynamic monitoring and scheduling of task execution state becomes difficult
Solution Approach 1:
The patent segments the task execution process into multiple checkpoint instructions distributed throughout the code. Each checkpoint creates a monitoring point that allows the system to dynamically check task state without disrupting overall execution. This segmentation enables both simple implementation (by inserting small checkpoint instructions) and effective monitoring (by creating multiple observation points).
Solution Approach 2:
The patent applies preliminary action by pre-defining checkpoint instructions at key locations in the code before task execution begins. These checkpoints are predetermined positions where monitoring will occur, allowing the system to prepare monitoring capabilities in advance while maintaining simple task execution flow. The checkpoints are embedded during code compilation or setup phase.
2Reliability
If full data redundancy processing is applied to all data, then data security and reliability are improved, but storage overhead and memory access power consumption increase
Solution Approach 1:
The patent applies local quality by differentiating data importance levels and applying redundancy processing selectively rather than uniformly. Critical data fields receive full redundancy protection (e.g., replica redundancy or ECC), while less critical fields receive reduced or no redundancy. This localized approach ensures data reliability for important information while minimizing storage overhead for less important data.
Solution Approach 2:
The patent changes the redundancy parameter based on data importance classification. For high-importance data, it uses higher redundancy levels (such as multiple replicas or strong error correction), while for low-importance data, it uses lower redundancy levels or none at all. This parameter adjustment optimizes the balance between reliability and storage efficiency.
3Reliability
If full data redundancy processing is applied to all data, then data security and reliability are improved, but memory access power consumption increases
Solution Approach 1:
The patent reduces memory access power consumption by applying redundancy processing only to critical data fields that require protection. By identifying and marking important bits or fields, the system performs redundancy operations locally only where necessary, rather than processing entire data structures uniformly. This selective approach significantly reduces the number of memory accesses required for redundancy operations.
Solution Approach 2:
The patent applies partial action by performing redundancy processing on only a subset of data (the important/critical portions) rather than all data. This partial processing approach provides sufficient reliability for critical information while avoiding the excessive power consumption that would result from processing entire data sets, achieving an optimal balance between protection and energy efficiency.
Data Source
AI summary
The disclosure provides a data processing device and method. The data processing device may include: a task configuration information storage unit and a task queue configuration unit. The task configuration information storage unit is configured to store configuration information of tasks. The task queue configuration unit is configured to configure a task queue according to the configuration information stored in the task configuration information storage unit. According to the disclosure, a task queue may be configured according to the configuration information.


