gFPC: A Self-Tuning Compression Algorithm

This paper presents and evaluates gFPC, a self-tuning implementation of the FPC compression algorithm for double-precision floating-point data. gFPC uses a genetic algorithm to repeatedly reconfigure four hash-function parameters, which enables it to adapt to changes in the data during compression. Self tuning increases the harmonic-mean compression ratio on thirteen scientific datasets from 22% to 28% with sixteen kilobyte hash tables and from 36% to 43% with one megabyte hash tables. Individual datasets

• Type: Conference
• Year: 2010
• Where: DCC
• Authors: Martin Burtscher, Paruj Ratanaworabhan
• Keywords: Computer Graphics, DCC 2010, Double-precision Floating-point Data, FPC Compression Algorithm, Hash Tables