Cluster Resource Utilization Analysis and Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Developers face challenges in understanding and optimizing the concurrency and resource utilization of parallel applications in distributed computer systems, as existing tools lack effective analysis and visualization capabilities to identify node contention and resource sharing patterns over time.
Innovation Solution
A method and tool for analyzing and visualizing how applications leverage nodes in a distributed system, providing insights into concurrency, node usage, and interference from other processes and libraries, allowing developers to identify contention and optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel applications are executed on distributed computer systems to improve performance, then computational speed and problem-solving capability are enhanced, but understanding and debugging resource utilization becomes more difficult
Solution Approach 1:
The patent introduces an intermediary analysis tool that acts as a mediator between the parallel application and the developer. This tool intercepts and analyzes runtime information about process execution, library usage, and node utilization, then presents this information in a comprehensible format. The intermediary translates complex distributed system behavior into actionable insights without requiring changes to the application code itself.
Solution Approach 2:
The patent replaces manual analysis methods (mechanical inspection of system behavior) with automated information gathering and visualization. Instead of developers manually tracking resource usage through logs or system monitors, the invention implements an automated system that collects runtime data, processes it, and generates visual representations of concurrency patterns and resource utilization automatically.
2Loss of information
If developers manually track and analyze resource usage in parallel applications, then understanding of concurrency behavior can be achieved, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent implements preliminary action by having the analysis tool continuously gather and process runtime information in the background during application execution. Rather than requiring post-execution analysis or interrupting the development process, the tool proactively collects data about process execution, library calls, and node utilization as the application runs, preparing insights before the developer needs them.
Solution Approach 2:
The analysis tool implements self-service by automatically gathering, processing, and presenting resource utilization information without requiring manual intervention. The system instruments itself to collect runtime data, automatically processes this information to identify concurrency patterns and resource contention, and generates visualizations autonomously, freeing the developer from manual tracking tasks.
3Ease of operation
If existing developer tools are used to analyze parallel applications, then basic debugging functionality is provided, but effective analysis and visualization of node contention and resource sharing patterns is lacking
Solution Approach 1:
The patent adds another dimension to traditional debugging tools by introducing visual representation of resource utilization over time. Instead of merely displaying tabular data or simple metrics, the invention creates temporal visualizations that show how resource usage patterns evolve during application execution, enabling developers to see concurrency behavior from a temporal perspective that traditional tools lack.
Solution Approach 2:
The patent introduces an intermediary analysis layer between the parallel application and the developer interface. This intermediary component gathers detailed runtime information about process execution, library usage, and node utilization, then transforms this raw data into meaningful visualizations. The intermediary acts as a bridge that translates complex system behavior into comprehensible graphical representations of resource contention and concurrency patterns.
Data Source
AI summary
An analysis and visualization depicts how an application is leveraging processor cores of a distributed computing system, such as a computer cluster, in time. The analysis and visualization enables a developer to readily identify the degree of concurrency exploited by an application at runtime and the amount of overhead used by libraries or middleware. Information regarding processes or threads running on the nodes over time is received, analyzed, and presented to indicate portions of computer cluster that are used by the application, idle, other processes, and libraries in the system. The analysis and visualization can help a developer understand or confirm contention for or under-utilization of system resources for the application and libraries.