Configurable Neural Network Processor for Dynamic Task Scheduling
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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 and resource utilization.
Innovation Solution
An online configurable neural network operation device and method that includes a control module and multiple operation units, allowing for dynamic task configuration and data transmission between units, enabling flexible and extensible processor operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If common launching mode is used to execute tasks, then task execution can be completed, but dynamic monitoring and scheduling of task execution state becomes difficult
Solution Approach 1:
The patent implements dynamic task configuration by allowing the control module to send configuration instructions to operation units during runtime. This enables the system to adaptively adjust task execution parameters and monitor execution states in real-time, resolving the contradiction between ease of operation and device complexity.
Solution Approach 2:
The patent establishes a feedback mechanism where the control module receives execution state information from operation units and uses this feedback to dynamically adjust task configuration. This closed-loop control enables effective monitoring and scheduling while maintaining manageable system complexity.
2Productivity
If dedicated processor core is used for neural network operations, then computation speed is improved, but flexibility and extensibility are reduced
Solution Approach 1:
The patent designs operation units that can be dynamically configured to perform different neural network operations. The control module receives configuration instructions and adjusts the operation units' functionality accordingly, enabling a single processor to handle multiple neural network algorithms and tasks, thus achieving both high computation speed and flexibility.
Solution Approach 2:
The patent changes the operational parameters of the processor by allowing dynamic configuration of operation units through control instructions. This enables the same hardware to adapt to different computation requirements by modifying parameters such as operation type, data flow patterns, and resource allocation, maintaining both speed and versatility.
3Productivity
If online configuration is implemented for different computation requirements, then processor utilization rate increases, but system complexity increases
Solution Approach 1:
The patent implements a self-service configuration mechanism where the control module autonomously processes configuration instructions and adjusts operation units without requiring complex external control systems. This simplifies the overall system architecture while enabling high processor utilization through online reconfiguration.
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.