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Auflistung nach Autor:in "Kissinger, Thomas"

1 - 4 von 4
  • Konferenzbeitrag
    Energy Elasticity on Heterogeneous Hardware using Adaptive Resource Reconfiguration
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Ungethüm, Annett; Kissinger, Thomas; Mentzel, Willi-Wolfram; Mier, Eric; Habich, Dirk; Lehner, Wolfgang
    Energy awareness of database systems has emerged as a critical research topic, because energy consumption is becoming a major factor. Recent energy-related hardware developments tend towards o ering more and more configuration opportunities for the software to control its own energy-based behavior. Existing research within the DB community so far mainly focused on leveraging this configuration spectrum to identify the most energy-efficient configuration for specific operators or entire queries. In [Un16], we introduced the concept of energy elasticity and proposed the energy-control loop as an implementation of this concept. Energy elasticity refers to the ability of software to behave energy-proportional and energy-e cient at the same time while maintaining a certain quality of service.
  • Textdokument
    NeMeSys – Energy Adaptive Graph Pattern Matching on NUMA-based Multiprocessor Systems
    (BTW 2019, 2019) Krause, Alexander; Ungethüm, Annett; Kissinger, Thomas; Habich, Dirk; Lehner, Wolfgang
    NeMeSys is a NUMA-aware graph pattern processing engine, which leverages intelligent resource management for energy adaptive processing. With modern server systems incorporating an increasing amount of main memory, we can store graphs and compute analytical graph algorithms like graph pattern matching completely in-memory. Such server systems usually contain several powerful multiprocessors, which come with a high demand for energy. We demonstrate, that graph patterns can be processed in given performance constraints while saving energy, which would be wasted without proper controlling.
  • Konferenzbeitrag
    Pack indexing for time-constrained in-memory query processing
    (Datenbanksysteme für Business, Technologie und Web (BTW) 2023, 2013) Jaekel, Tobias; Voigt, Hannes; Kissinger, Thomas; Lehner, Wolfgang
    Main memory databases management systems are used more often and in a wide spread of application scenarios. To take significant advantage of the main memory read performance, most techniques known from traditional disk-centric database systems have to be adapted and re-designed. In the field of indexing, many mainmemory-optimized index structures have been proposed. Most of these works aim at primary indexing. Secondary indexes are rarely considered in the context of main memory databases. Either query performance is sufficiently good without secondary indexing or main memory is a resource too scarce to invest in huge secondary indexes. A more subtle trade between benefit and costs of secondary indexing has not been considered so far. In this paper we present Pack Indexing, a secondary indexing technique for main memory databases that allows a precise trade-off between the benefit in query execution time gained with a secondary index and main memory invested for that index. Compared to traditional indexing, Pack Indexing achieves this by varying the granularity of indexing. We discuss the Pack Indexing concept in detail and describe how the concept can be implemented. To demonstrate the usefulness and the effectiveness of our approach, we present several experiments with different datasets.
  • Konferenzbeitrag
    Plan Operator Specialization using Reflective Compiler Techniques
    (Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Hänsch, Carl-Philip; Kissinger, Thomas; Habich, Dirk; Lehner, Wolfgang
    Query-specific code generation has become a well-established approach to speed up query execution. However, this approach has two major drawbacks: (1) code generators are in general hard to write and maintain, (2) code generators lack the ability to deal with custom operators. To overcome these limitations, we suggest to return to the traditional execution approach with precompiled generic operators which are parametrized and composed to query plans at query compile time. Nevertheless, to optimize such plan operators and speed up their execution, we introduce a novel specialization approach using reflective compiler techniques. Employing code annotations and an additional compiler pass, we are able to track and replace low-level load instructions that refer to operator parameters which remain constant during execution time. By dissolving such up-to-now unknown constant variables, the compiler can further optimize the code and is able to determine query-specific optimized operators out of generic operator code. In our evaluation, we show that our approach speeds up the execution of the traditional generic operator approach in terms of execution time without facing the drawbacks of code generators.