Efficient Parallel Text Compression on GPUs

Abstract

This paper demonstrates an efficient text compressor with parallel Lempel-Ziv-Markov chain algorithm (LZMA) on graphics processing units (GPUs). We divide LZMA into two parts, match finder and range encoder. We parallel both parts and achieve competitive performance with freeArc on AMD 6-core 2.81 GHz CPU. We measure match finder time, range encoder compression time and demonstrate realtime performance on a large dataset: 10 GB web pages crawled by IRLbot. Our parallel range encoder is 15 times faster than sequential algorithm (FastAC) with static model.