Unified Profiler Visualizing Cross-Subsystem Performance Data
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Solution Overview
Problem
Current profiler tools face challenges in navigating and correlating performance data from different runtime environment subsystems, making it difficult for developers to identify and address performance issues across multiple subsystems effectively.
Innovation Solution
The development of tools and techniques that allow for the collection and visualization of integrated performance data from various subsystems, enabling users to perform visual queries and drill down into specific programming elements contributing to performance problems, thereby correlating issues with the relevant code for modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If profiler tools collect performance data from multiple runtime environment subsystems, then the comprehensiveness of performance information is improved, but the complexity of navigating and correlating the data increases
Solution Approach 1:
The patent combines performance data from multiple runtime environment subsystems (graphics, media decoding, networking, etc.) into a unified profiler interface. The system merges data from different sources and presents them together in a single visualization model, allowing developers to view comprehensive performance information without manually switching between multiple tools or data sources.
Solution Approach 2:
The profiler acts as an intermediary layer between the complex subsystems and the developer. It collects, processes, and correlates data from various subsystems, then presents simplified views through visualization models. The system provides intermediate processing steps including data integration, correlation, and navigation assistance to bridge the gap between raw subsystem data and actionable insights.
2Measurement precision
If the profiler provides detailed performance data from all subsystems, then the precision of performance measurement is improved, but the difficulty of detecting and measuring specific issues increases
Solution Approach 1:
The profiler divides the complex performance data into organized segments or categories corresponding to different subsystems and performance aspects. The visualization model presents data in structured segments that can be individually explored, allowing developers to systematically navigate through different areas rather than facing a wall of undifferentiated data.
Solution Approach 2:
The system transforms performance data into visual dimensions through graphs, charts, and other visual representations. By converting numerical performance metrics into visual forms with spatial dimensions, the profiler makes it easier to detect patterns, anomalies, and correlations that would be difficult to identify in raw tabular data.
3Ease of operation
If the system integrates data from multiple subsystems into a unified view, then the ease of operation is improved, but the device complexity increases
Solution Approach 1:
The profiler is designed as a universal tool that can handle multiple types of performance data from different subsystems through a single interface. The system provides multi-functional capabilities including data collection, visualization, correlation, and navigation all within one unified tool, eliminating the need for multiple specialized tools and simplifying the developer workflow.
Data Source
AI summary
Performance data can be collected from different runtime environment subsystems of a computer system while the computer system is running a program in the runtime environment. A visualization model can be displayed, and a visual query of the integrated data can be received at the visualization model. Queried data can be compiled and displayed in response to the visual query. The queried data can be drilled into in response to user input. In response to a navigation request, navigation can lead to a programming element related to a portion of the queried data.