Parallel Execution Scenario Generation for Hardware Exception Handling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing the execution of computer tasks under time constraints in computer processing systems is challenging due to difficulties in identifying and mitigating hardware exceptions, which can lead to delays and unreliable operations.
Innovation Solution
A computer-implemented method that identifies a computer task, determines a hardware exception source, an exception unit, and a parallelization factor to recommend a parallel execution scenario, allowing for efficient execution across multiple computer units to minimize exception recurrence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computer tasks are executed under time constraints, then productivity is improved, but reliability deteriorates due to hardware exceptions and delays
Solution Approach 1:
The system performs preliminary identification of hardware exception sources and determines exception units before task execution. By pre-analyzing potential exception sources and establishing parallelization factors in advance, the system prepares mitigation strategies proactively, allowing tasks to be executed under time constraints while maintaining reliability through pre-planned exception handling.
Solution Approach 2:
The system segments the computer task into multiple parallel execution scenarios based on identified exception units and parallelization factors. By dividing the task into independent parallel segments that can be executed simultaneously on different computer units, the system achieves both improved productivity through parallel processing and enhanced reliability by isolating potential exception impacts to specific segments.
2Reliability
If hardware exceptions are monitored and mitigated, then reliability is improved, but device complexity increases
Solution Approach 1:
The system implements self-service exception handling by automatically identifying hardware exception sources, determining exception units, and generating parallel execution scenarios without requiring external intervention. The system monitors itself for exceptions and autonomously adjusts execution strategies, improving reliability while minimizing the complexity burden on external control systems.
Solution Approach 2:
The system changes execution parameters dynamically by determining parallelization factors based on identified exception units. Instead of adding complex hardware exception handling mechanisms, the system adjusts software execution parameters such as parallelization degree and task distribution to mitigate exceptions, achieving improved reliability through parameter optimization rather than structural complexity.
3Productivity
If parallel execution scenarios are implemented, then productivity is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The system introduces an intermediary exception analysis component that bridges the gap between parallel execution scenarios and exception detection. This intermediary layer correlates hardware exceptions with specific parallel execution units and tracks exception propagation across parallel segments, enabling effective monitoring and measurement of exceptions in parallel environments without compromising productivity.
Data Source
AI summary
A computer-implemented method comprises identifying a computer task; determining a hardware exception source associated with the computer task; determining an exception unit associated with the hardware exception source; determining a parallelization factor associated with the hardware exception source; and determining a parallel execution scenario associated with the computer task based on the exception unit and the parallelization factor. A corresponding computer program product and computer system are also disclosed.