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Abstract
ObjectiveThe purpose of this work is to optimize the processing of molecular dynamics (MD) trajectory data obtained for large biomolecular systems. Two popular software tools were chosen as the reference: the tng and the xdrfile libraries. Current implementation of tng algorithms and library is either fast or storage efficient and xdrfile is storage efficient but slow. Our aim was to combine speed and storage efficiency through the xdrfile’s code modification.ResultsHere we present libxtc, a ready-to-use library for reading MD trajectory files in xtc format. The effectiveness of libxtc is demonstrated for several biomolecular systems of various sizes (~ 2 × 104 to ~ 2 × 105 atoms). In sequential mode, the performance of libxtc is up to 1.8 times higher and 1.4 times lower than xdrfile and tng, respectively. In parallel mode, libxtc is about 3 and 1.3 times faster than xdrfile and tng. At the same time, MD data stored in the xtc format require about 1.3 times less disk space than those treated with the tng algorithm in the fastest reading mode, which is a noticeable saving especially when the MD trajectory is long and the number of atoms is large—this applies to most biologically relevant systems.
Highlights
Molecular dynamics (MD) is one of the most powerful and widely used methods for atomistic modeling of biological systems
Here we present libxtc, a ready-to-use library for reading MD trajectory files in xtc format
MD data stored in the xtc format require about 1.3 times less disk space than those treated with the tng algorithm in the fastest reading mode, which is a noticeable saving especially when the MD trajectory is long and the number of atoms is large—this applies to most biologically relevant systems
Summary
To test the optimization techniques implemented in the library, we compared the performance of libxtc, xdrfile and tng using MD trajectories obtained for the molecular systems enumerated in Additional file 1: Table S1. The test systems were selected based on the following criteria They represent real cases that are commonly considered in biomolecular simulations. Overall processing time is typically not too sensitive to the trajectory formats and compression algorithms. The results obtained are shown in Additional file 1: Table S3 and Figure S1. The second set of tests is aimed at measuring the dependence of the performance of libxtc on the number of CPUs (Additional file 1: Figure S1). Only the decompression time was taken into account due to the aforementioned observation that measurement results are significantly influenced by the hardware. The tng and xdrfile acceleration data are not shown, due to the single threaded structure of their code
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