APU Register Extraction for Pre-Reset Hang Recovery Debugging
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Solution Overview
Problem
Conventional methods for debugging hangs in accelerated processing units (APUs) are limited by the amount of information that can be extracted from the APU output buffer before reset, hindering efficient diagnosis and resolution of the failure cause.
Innovation Solution
Employing a machine learning or heuristics-based algorithm at the APU processor to selectively extract data from registers within the processing pipeline in real-time, allowing for more detailed information about the hang to be obtained before reset, thereby enhancing the debug process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional methods extract data only from APU output buffer before reset, then the extraction process is simple and fast, but the amount of diagnostic information obtained is limited
Solution Approach 1:
The patent extracts diagnostic information from multiple sources including APU output buffer, register files, and internal processing stages. By taking out data from these previously inaccessible locations, the system obtains comprehensive diagnostic information about the hang condition without requiring complex external analysis tools
Solution Approach 2:
The data extraction process is segmented into multiple stages: extracting from output buffer, extracting from register files, and extracting from intermediate processing stages. This segmentation allows the system to gather information from different parts of the APU pipeline systematically, maximizing diagnostic value while maintaining manageable complexity
2Reliability
If the APU is reset immediately upon hang detection, then system stability is maintained, but detailed information about the hang cause is lost
Solution Approach 1:
The system performs preliminary data extraction actions before the APU reset is executed. By capturing diagnostic information from register files and processing stages in advance of the reset, the system preserves crucial hang cause information while still maintaining system stability through timely reset
Solution Approach 2:
The extracted diagnostic information is fed back to developers and debugging tools, providing actionable insights about the hang cause. This feedback loop enables faster identification and resolution of issues, reducing overall debugging time while maintaining system reliability
3Measurement precision
If comprehensive data is extracted from all APU registers, then diagnostic accuracy is improved, but the processing time and resource usage increase
Solution Approach 1:
The system applies different extraction strategies to different parts of the APU based on their diagnostic value. High-priority registers and processing stages that are most likely to contain hang cause information are extracted with higher fidelity, while less critical areas receive minimal extraction, optimizing the balance between accuracy and efficiency
Data Source
AI summary
A processing system includes a driver and an accelerated processing unit including a processor. The processor is configured to initiate a status check of wavefronts being executed by the accelerated processing unit responsive to receiving a status inquiry from the driver. Responsive to the status check indicating a hang, the processor is configured to employ a machine learning algorithm to selectively extract data from one or more registers of the accelerated processing unit. For example, in some cases, the one or more registers are local to one or more compute units of the accelerated processing unit. The processor is further configured to export the data from the accelerated processing unit prior to the accelerated processing unit being reset.