{'fraction_non_alphanumeric': 0.01707455890722823, 'fraction_numerical': 0.006829823562891292, 'mean_word_length': 5.684410646387833, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Efficient and Accuracy-Ensured Waveform Compression for Transient Circuit Simulation

Efficient and accurate waveform compression is essentially important for the application of analog circuit transition simulation nowadays. In this article, an analog waveform compression scheme is proposed which includes two compressed formats for representing small and large signal values, respectively. The compressed formats and the corresponding compression/decompression approaches ensure that both the absolute and relative errors of each signal value restored from the compression are within specified criteria. The formats are integrated in a block-by-block compressing procedure which facilitates a secondary lossless compression and a three-stage pipeline scheme for fast conversion from the simulator’s output to the compressed hard-disk file. Theoretical analysis is presented to prove the accuracy-ensured property of our approach. Two schemes are also proposed to incorporate the prediction method. They achieve larger compression ratio for some cases while preserving the accuracy and runtime efficiency. Experiments are carried out with voltage waveforms from industrial circuits. The results validate the accuracy and the efficiency of the proposed techniques. The obtained compression ratio is 2.6X larger than existing work without overhead, even though the latter induces much larger error. Compared with the original double-precision floating number format, the proposed approach achieves the compression ratio of 26 averagely and up to 70, while keeping the relative error less than 10−3 and absolute error less than 10−5. And with the pipelined computation, the proposed compression approach hardly increases time cost to the transient simulation.