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  • Habich, Dirk  (2)
  • Mathematics  (2)
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  • 1
    Online Resource
    Online Resource
    From a Comprehensive Experimental Survey to a Cost-based Selection Strategy for Lightweight Integer Compression Algorithms
    Association for Computing Machinery (ACM) ; 2019
    In:  ACM Transactions on Database Systems Vol. 44, No. 3 ( 2019-09-30), p. 1-46
    Details
    In: ACM Transactions on Database Systems, Association for Computing Machinery (ACM), Vol. 44, No. 3 ( 2019-09-30), p. 1-46
    Abstract: Lightweight integer compression algorithms are frequently applied in in-memory database systems to tackle the growing gap between processor speed and main memory bandwidth. In recent years, the vectorization of basic techniques such as delta coding and null suppression has considerably enlarged the corpus of available algorithms. As a result, today there is a large number of algorithms to choose from, while different algorithms are tailored to different data characteristics. However, a comparative evaluation of these algorithms with different data and hardware characteristics has never been sufficiently conducted in the literature. To close this gap, we conducted an exhaustive experimental survey by evaluating several state-of-the-art lightweight integer compression algorithms as well as cascades of basic techniques. We systematically investigated the influence of data as well as hardware properties on the performance and the compression rates. The evaluated algorithms are based on publicly available implementations as well as our own vectorized reimplementations. We summarize our experimental findings leading to several new insights and to the conclusion that there is no single-best algorithm. Moreover, in this article, we also introduce and evaluate a novel cost model for the selection of a suitable lightweight integer compression algorithm for a given dataset.
    Type of Medium: Online Resource
    ISSN: 0362-5915 , 1557-4644
    URL: Article
    DOI: 10.1145/3323991
    RVK:
    SA 2960
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2019
    detail.hit.zdb_id: 196155-X
    detail.hit.zdb_id: 2006335-0
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  • 2
    Online Resource
    Online Resource
    Partition-based SIMD Processing and its Application to Columnar Database Systems
    Springer Science and Business Media LLC ; 2023
    In:  Datenbank-Spektrum Vol. 23, No. 1 ( 2023-03), p. 53-63
    Details
    In: Datenbank-Spektrum, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2023-03), p. 53-63
    Abstract: The Single Instruction Multiple Data (SIMD) paradigm became a core principle for optimizing query processing in columnar database systems. Until now, only the instructions are considered to be efficient enough to achieve the expected speedups, while avoiding is considered almost imperative. However, the instruction offers a very flexible way to populate SIMD registers with data elements coming from non-consecutive memory locations. As we will discuss within this article, the instruction can achieve the same performance as the instruction, if applied properly. To enable the proper usage, we outline a novel access pattern allowing fine-grained, partition-based SIMD implementations. Then, we apply this partition-based SIMD processing to two representative examples from columnar database systems to experimentally demonstrate the applicability and efficiency of our new access pattern.
    Type of Medium: Online Resource
    ISSN: 1618-2162 , 1610-1995
    URL: Article
    DOI: 10.1007/s13222-022-00431-0
    RVK:
    SA 4490
    RVK:
    SQ 1100
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2211679-5
    detail.hit.zdb_id: 2060239-X
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