Lock Contention Analysis Using HITS Algorithm
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Solution Overview
Problem
Complex computing systems face challenges in identifying and addressing lock contention inefficiencies, which lead to operation latency and reduced concurrency, due to the complexity of analyzing multiple threads, locks, and interdependencies in large-scale systems.
Innovation Solution
The use of data analysis and visualization techniques, such as plotting blocking relationships into graphs and applying algorithms like HITS and PageRank, to identify key processes causing lock contention and quantify their impact, allowing for efficient identification and optimization of bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional analysis methods are used to identify lock contention issues in complex computing systems, then comprehensive analysis can be performed, but the analysis becomes extremely time-consuming and difficult due to the large number of processes and interdependencies
Solution Approach 1:
The patent extracts and isolates only the critical lock contention relationships from the complex system data using automated analysis. By focusing on extracting specific blocking relationships and representing them in a simplified visual format, the system identifies key issues without requiring analysis of all system components, thus reducing analysis time while maintaining identification accuracy.
Solution Approach 2:
The patent creates a simplified visual representation (copy) of the lock contention relationships that mirrors the essential blocking patterns without replicating the full complexity of the underlying system. This visual model allows rapid identification of key contention issues without requiring deep analysis of all process interdependencies.
2Measurement precision
If detailed analysis of all processes and interdependencies is performed to identify lock contention bottlenecks, then accurate identification can be achieved, but the complexity of the analysis increases significantly
Solution Approach 1:
The patent segments the complex system analysis into distinct visual components representing different lock contention relationships. By dividing the analysis into separate visual elements that can be independently examined, the system maintains identification accuracy while reducing the perceived and actual complexity of the overall analysis.
Solution Approach 2:
The patent transforms the complex multi-dimensional process interdependency data into a two-dimensional visual representation. This dimensional transformation allows key lock contention relationships to be identified through visual inspection rather than complex multi-variable analysis, reducing analysis complexity while preserving identification accuracy.
3Power
If more processing resources are added to improve system performance, then computational power increases, but lock contention bottlenecks remain and continue to degrade user experience
Solution Approach 1:
The patent enables preliminary identification of lock contention bottlenecks before they severely impact system performance. By providing early warning and clear identification of problematic processes and locking patterns, the system allows proactive optimization of code and locking mechanisms, preventing the waste of processing power on bottlenecked operations and maintaining higher overall productivity.
Data Source
AI summary
A system is described for identifying key lock contention issues in computing devices. A computing device is executed and lock contention information relating to operations during execution of the computing device is recorded. The data is parsed and analyzed to determine blocking relationships between operations due to lock contention. Algorithms are implemented to analyze dependencies between operations based on the data and to identify key areas of optimization for performance improvement. Algorithms can be based on the Hyperlink-Induced Topic Search algorithm or the PageRank algorithm.