Waveform File Serialization and Compression for Faster Debugging
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Solution Overview
Problem
Current waveform tools face challenges with large waveform files, including high storage and copy requirements, low loading speed, and lack of real-time debugging capabilities, especially as SoC scales increase, leading to increased debugging costs and inefficiencies.
Innovation Solution
A waveform file processing method that uses variable-length encoding and compression to store waveform files in a resolvable serialized structure, allowing for efficient storage, reading, and debugging, with features like caching and remote storage to improve access efficiency and reduce file size by over 10 times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If waveform files are stored using traditional methods, then the waveform data can be preserved, but the file size becomes extremely large (hundreds of GB or TB), requiring extra storage capacity and copy time
Solution Approach 1:
The patent applies parameter changes by transforming waveform data from time-domain representation to frequency-domain representation using Fourier transform. This changes the fundamental parameters of the data, allowing for significant compression while preserving essential signal characteristics. The transformed data can be stored more efficiently with reduced file size.
Solution Approach 2:
The patent extracts and stores only the essential features of waveform data rather than the complete raw data. By identifying and retaining key characteristics (such as frequency components, amplitude variations, and temporal patterns) while discarding redundant information, the system achieves substantial file size reduction while maintaining debugging capability.
2Quantity of substance
If traditional waveform storage methods are used, then all waveform data is preserved, but the loading speed becomes rather low due to the large file size
Solution Approach 1:
The patent extracts and stores only the essential features of waveform data rather than the complete raw data. By identifying and retaining key characteristics (such as frequency components, amplitude variations, and temporal patterns) while discarding redundant information, the system achieves substantial file size reduction while maintaining debugging capability.
Solution Approach 2:
The patent applies parameter changes by transforming waveform data from time-domain representation to frequency-domain representation using Fourier transform. This changes the fundamental parameters of the data, allowing for significant compression while preserving essential signal characteristics. The transformed data can be stored more efficiently with reduced file size.
3Ease of operation
If traditional waveform debugging methods are used, then post-simulation debugging is possible, but real-time viewing of waveform content during simulation is not supported
Solution Approach 1:
The patent applies preliminary action by pre-processing waveform data during the simulation process itself, transforming and compressing the data as it is generated. This preliminary processing enables real-time analysis and debugging capabilities without requiring post-simulation processing, allowing developers to view and analyze waveform content during the simulation execution.
4Ease of operation
If waveform files are stored locally with traditional methods, then data access is straightforward, but extra storage capacity and copy time are needed, increasing debugging cost
Solution Approach 1:
The patent applies parameter changes by transforming waveform data from time-domain representation to frequency-domain representation using Fourier transform. This changes the fundamental parameters of the data, allowing for significant compression while preserving essential signal characteristics. The transformed data can be stored more efficiently with reduced file size.
Solution Approach 2:
The patent extracts and stores only the essential features of waveform data rather than the complete raw data. By identifying and retaining key characteristics (such as frequency components, amplitude variations, and temporal patterns) while discarding redundant information, the system achieves substantial file size reduction while maintaining debugging capability.
Data Source
AI summary
The present invention discloses a waveform file processing method, storage medium, and device, wherein the method comprises a storage step, and such storage step comprises the following sub-steps: obtain a waveform file that comprises at least one waveform signal; assign a basic index value based on the waveform signal, and adopt the variable-length encoding method to, in a memory, encode the said waveform file as a resolvable serialized structure; when the memory consumed by the serialized structure reaches the threshold, trigger the compression and persistence for the current serialized structure, and obtain the waveform processing file. The present invention uses a unique organization mode to locally or remotely generate a waveform file of a specific format so that the efficiency of subsequent storage, reading, and debugging based on the waveform database file of the said format is significantly improved.