Received March 5, 2020, accepted April 27, 2020, date of publication April 29, 2020, date of current version May 14, 2020. Digital Object Identifier 10.1109/ACCESS.2020.2991314 High-Throughput Variable-to-Fixed Entropy Codec Using Selective, Stochastic Code Forests MANUEL MARTÍNEZ TORRES 1, MIGUEL HERNÁNDEZ-CABRONERO 2, IAN BLANES 2, (Senior Member, IEEE), AND JOAN SERRA-SAGRISTÀ 2, (Senior Member, IEEE) 1Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany 2Information and Communications Engineering, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain Corresponding author: Miguel Hernández-Cabronero (
[email protected]) This was supported in part by the Postdoctoral Fellowship Program Beatriu de Pinós through the Secretary of Universities and Research (Government of Catalonia) under Grant 2018-BP-00008, in part by the Horizon 2020 Program of Research and Innovation of the European Union under the Marie Skªodowska-Curie under Grant 801370, in part by the Spanish Government under Grant RTI2018-095287-B-I00, and in part by the Catalan Government under Grant 2017SGR-463. ABSTRACT Efficient high-throughput (HT) compression algorithms are paramount to meet the stringent constraints of present and upcoming data storage, processing, and transmission systems. In particular, latency, bandwidth and energy requirements are critical for those systems. Most HT codecs are designed to maximize compression speed, and secondarily to minimize compressed lengths. On the other hand, decompression speed is often equally or more critical than compression speed, especially in scenarios where decompression is performed multiple times and/or at critical parts of a system. In this work, an algorithm to design variable-to-fixed (VF) codes is proposed that prioritizes decompression speed.