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| Página principal > Artículos > Artículos publicados > High-throughput variable-to-fixed entropy codec using selective, stochastic code forests |
| Fecha: | 2020 |
| Resumen: | 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. Stationary Markov analysis is employed to generate multiple, jointly optimized codes (denoted code forests). Their average compression efficiency is on par with the state of the art in VF codes, e. g. , within 1% of Yamamoto et al. 's algorithm. The proposed code forest structure enables the implementation of highly efficient codecs, with decompression speeds 3. 8 times faster than other state-of-the-art HT entropy codecs with equal or better compression ratios for natural data sources. Compared to these HT codecs, the proposed forests yields similar compression efficiency and speeds. |
| Ayudas: | European Commission 801370 Generalitat de Catalunya 2017/SGR-463 Generalitat de Catalunya 2018/BP-00008 Agencia Estatal de Investigación RTI2018-095287-B-I00 |
| Nota: | This was supported in part by the Postdoctoral Fellowship Program Beatriu de Pin\u00F3s 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 Sk\u0142odowska-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. |
| Derechos: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. |
| Lengua: | Anglès |
| Documento: | Article ; recerca ; Versió publicada |
| Publicado en: | IEEE Access, Vol. 8 (2020) , p. 81283-81297, ISSN 2169-3536 |
15 p, 9.1 MB |