# Parallel decompression of gzip-compressed files and random access to DNA sequences

## TL;DR

This paper introduces pugz, a parallel decompression algorithm for gzip files, significantly speeding up decompression and enabling near-random access to DNA sequences in compressed files, addressing a key bottleneck in large-scale sequencing data analysis.

## Contribution

The paper presents a novel parallel decompression method and implementation, pugz, that outperforms existing tools and explores random access in gzip-compressed DNA data files.

## Key findings

- pugz is 10x faster than gunzip
- pugz is 5x faster than libdeflate
- random access is feasible at low compression levels

## Abstract

Decompressing a file made by the gzip program at an arbitrary location is in principle impossible, due to the nature of the DEFLATE compression algorithm. Consequently, no existing program can take advantage of parallelism to rapidly decompress large gzip-compressed files. This is an unsatisfactory bottleneck, especially for the analysis of large sequencing data experiments. Here we propose a parallel algorithm and an implementation, pugz, that performs fast and exact decompression of any text file. We show that pugz is an order of magnitude faster than gunzip, and 5x faster than a highly-optimized sequential implementation (libdeflate). We also study the related problem of random access to compressed data. We give simple models and experimental results that shed light on the structure of gzip-compressed files containing DNA sequences. Preliminary results show that random access to sequences within a gzip-compressed FASTQ file is almost always feasible at low compression levels, yet is approximate at higher compression levels.