Make larger vector register sizes new challenges? Lessons learned from the area of vectorized lightweight compression algorithms
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
The exploitation of data as well as hardware properties is a core aspect for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, in-memory data processing also benefits from novel processing concepts based on lightweight compressed data. To speed up compression as well as decompression, an active research field deals with the specialization of these algorithms to hardware features such as vectorization using SIMD instructions. Most of the vectorized implementations have been proposed for 128 bit vector registers. However, hardware vendors still increase the vector register sizes, whereby a straightforward transformation to these wider vector sizes is possible in most-cases. Thus, we systematically investigated the impact of different SIMD instruction set extensions with wider vector sizes on the behavior of straightforward transformed implementations. In this paper, we will describe our evaluation methodology and present selective results of our exhaustive evaluation. In particular, we will highlight some challenges and present first approaches to tackle them.
Details
Originalsprache | Englisch |
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Titel | DBTest'18: Proceedings of the Workshop on Testing Database Systems |
Herausgeber (Verlag) | Association for Computing Machinery (ACM), New York |
Seiten | 1-6 |
ISBN (elektronisch) | 978-1-4503-5826-2 |
Publikationsstatus | Veröffentlicht - 15 Juni 2018 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | MOD: International Conference on Management of Data (DBTest) |
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Konferenz
Titel | 2018 Workshop on Testing Database Systems, DBTest 2018 |
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Dauer | 15 Juni 2018 |
Stadt | Houston |
Land | USA/Vereinigte Staaten |
Externe IDs
Scopus | 85059944117 |
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ORCID | /0000-0001-8107-2775/work/142253479 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Database systems, Experimental evaluation, In-memory, Lightweight data compression, Vectorization