Data as well as hardware characteristics are two key aspects for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, efficient in-memory processing benefits from novel processing concepts based on lightweight compressed data. Thus, an active research field deals with the adaptation of new hardware features such as vectorization using SIMD instructions to speedup lightweight data compression algorithms. Following this trend, we propose a novel approach for run-length encoding, a well-known and often applied lightweight compression technique. Our novel approach is based on newly introduced conflict detection (CD) instructions in Intel's AVX-512 instruction set extension. As we are going to show, our CD-based approach has unique properties and outperforms the state-of-the-art RLE approach for data sets with small run lengths.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:82179 |
Date | 18 January 2023 |
Creators | Lehner, Wolfgang, Ungethum, Annett, Pietrzyk, Johannes, Damme, Patrick, Habich, Dirk |
Publisher | IEEE |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 978-1-5386-6306-6, 10.1109/ICDEW.2018.00023, info:eu-repo/grantAgreement/Deutsche Forschungsgemeinschaft/Collaborative Research Center 912/164481002//HAEC - Highly Adaptive Energy-Efficient Computing/SFB 912 |
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