Waveform Data Reduction for Interactive EDA Visualization
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Solution Overview
Problem
Modern EDA tools face performance issues in handling massive quantities of waveform data, leading to difficulties in maintaining interactive performance during waveform visualization due to the need to process large amounts of data quickly.
Innovation Solution
Implementing a data reduction method that filters and scales waveform data to create a reduced set, retaining salient points and discarding extraneous data, allowing for efficient processing by the graphics processing unit (GPU) to enhance interactive performance without compromising data fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional waveform viewing tools process all waveform data points for display, then data fidelity is maintained, but processing speed and interactive performance deteriorate
Solution Approach 1:
The patent extracts only the essential data points needed for accurate waveform representation. By identifying and removing redundant data points that do not contribute to the visual accuracy or analytical value of the waveform, the system maintains data fidelity while significantly reducing the processing burden. This extraction approach allows the tool to focus computational resources on the most critical data elements.
Solution Approach 2:
The patent dynamically adjusts processing parameters based on the selected time window and display requirements. By changing parameters such as data point sampling rate, reduction ratio, and processing depth according to the specific viewing context, the system optimizes the balance between data fidelity and processing speed for each interaction scenario.
2Ease of operation
If all waveform data is loaded into memory for interactive manipulation, then complete data access is available, but memory consumption and processing overhead increase
Solution Approach 1:
The patent segments the waveform data into manageable portions based on the user's selected time window and display requirements. Instead of loading the entire waveform dataset into memory, the system divides and loads only the relevant segments needed for the current view, enabling efficient interactive manipulation while minimizing memory consumption.
Solution Approach 2:
The patent performs preliminary data reduction and preprocessing operations before the user interacts with the waveform data. By pre-identifying and retaining only the essential data points that will be needed for display and analysis, the system reduces the amount of data that needs to be loaded into memory during interactive sessions, thereby lowering memory consumption while maintaining ease of operation.
3Productivity
If waveform data is reduced to improve processing speed, then interactive performance improves, but data fidelity may be compromised
Solution Approach 1:
The patent replaces traditional mechanical data processing approaches with GPU-based parallel processing. This substitution enables the system to handle larger datasets and perform more sophisticated data reduction algorithms in real-time, achieving both high interactive performance and data fidelity through the superior computational capabilities of the GPU architecture.
Data Source
AI summary
An improved approach is provided to generate and display waveform data, where data reduction is intelligently applied to create filtered waveform data. By reducing the quantity of the waveform data in an intelligent manner, this permits the waveform display tool to process the waveforms quickly enough for interactive usage, while still retaining sufficient data fidelity for accurate data analysis and waveform visualization.