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Compressing molecular dynamics trajectories: Breaking the one-bit-per-sample barrier.

Jan Huwald¹, Stephan Richter¹, Bashar Ibrahim¹

¹Biosystem Analysis Research Group, Department of Mathematics and Computer Science, Jena Centre for Bioinformatics, Friedrich Schiller University, Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.

Journal of Computational Chemistry

|May 19, 2016

Summary

We developed a high resolution trajectory compression scheme (HRTC) that significantly reduces molecular dynamics data storage needs. This method compresses trajectory data to less than one bit per sample, outperforming current methods.

Keywords:

HRTC TNG library compression molecular dynamics trajectory

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Area of Science:

Computational Chemistry
Biophysics
Materials Science

Background:

Molecular dynamics simulations generate vast amounts of trajectory data.
Efficient data compression is crucial for storage and accessibility.
Current methods often combine quantization and Huffman encoding.

Purpose of the Study:

To introduce a novel, highly efficient trajectory compression algorithm.
To improve upon the state-of-the-art in molecular dynamics data compression.
To enable real-time data storage and analysis.

Main Methods:

Developed the High Resolution Trajectory Compression (HRTC) scheme.
Utilized piecewise linear functions for approximating quantized trajectories.
Implemented an error budget strategy balancing quantization and approximation.

Main Results:

HRTC achieves compression ratios several orders of magnitude better than state-of-the-art methods.
The algorithm compresses data to less than one bit per sample.
The method is computationally efficient and suitable for integration into simulation loops.

Conclusions:

HRTC offers a significant advancement in molecular dynamics data compression.
The scheme enables efficient storage and accessibility of large trajectory datasets.
HRTC can become the primary representation for trajectory data.