Mixed-Signal Waveform Block Compression for Fast Lossless Readout
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Solution Overview
Problem
Current data compression schemes for mixed signal environments in SoC design result in highly compressed waveforms with increased read times and potential data loss, especially for high-resolution and high-frequency signals, making it difficult to efficiently store and access large signal output waveforms for analysis.
Innovation Solution
A method involving the separation of signal waveforms into blocks, identification of shared time and signal portions, and selection of formats based on block size and read time, allowing for adaptive lossless compression that balances compressibility and readout latency by using hybrid data block formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If aggressive compression techniques are used to reduce waveform file size, then storage efficiency is improved, but read time increases and data loss occurs for high-resolution and high-frequency signals
Solution Approach 1:
The patent divides waveform data into multiple blocks, where each block can be independently compressed and stored. This segmentation allows the system to apply different compression strategies to different blocks based on their characteristics, enabling efficient storage while maintaining fast access to specific blocks without reading the entire file.
Solution Approach 2:
The patent applies different compression formats and strategies to different blocks based on local characteristics such as signal frequency, resolution requirements, and access patterns. High-frequency and high-resolution blocks use formats that preserve data integrity, while other blocks use more aggressive compression, optimizing both storage efficiency and read performance for each local region.
2Quantity of substance
If highly compressed waveforms are stored to reduce file size, then storage efficiency is improved, but multiple metadata references are created that increase read time
Solution Approach 1:
The patent extracts metadata from the compressed waveform data and stores it separately in a structured format. This separation reduces the complexity of metadata references within the compressed data stream, making it easier to navigate and access waveform data without having to parse through multiple nested metadata structures.
3Quantity of substance
If compression is applied to reduce data size, then storage efficiency is improved, but lossless data recovery becomes more difficult especially for high-resolution signals
Solution Approach 1:
The patent changes compression parameters dynamically based on signal characteristics such as frequency, amplitude, and resolution requirements. For high-resolution and high-frequency signals, the system uses parameters that ensure lossless compression, while for other signals, more aggressive compression is applied, thus maintaining data recovery accuracy where critical while achieving compression elsewhere.
Data Source
AI summary
A method including separating multiple signal waveforms into multiple blocks forming a sequence is provided. Each of the blocks includes at least a portion of each of the multiple signal waveforms. The method includes identifying a shared time portion and a shared signal portion for the signal waveforms within a first block from the multiple blocks and selecting a format for the first block based on a block size of the first block and a block read time of the first block. The method also includes compressing data in the first block based on the shared time portion, the shared signal portion, a preceding block and a subsequent block in the sequence, and storing the first block in a memory based on the format selected for the first block.