The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

Query execution techniques in database systems are constantly adapting to novel hardware
features in order to improve query performance, in particular for analytical queries. In the last …

Integer compression plays an important role in columnar database systems to reduce the
main memory footprint as well as to speedup query processing. To keep the additional …

Abstract The Single Instruction Multiple Data (SIMD) paradigm became a core principle for
optimizing query processing in columnar database systems. Until now, only the …

Exploiting parallelism is the name of the game for executing analytical queries with low
latency in in-memory database engines. Most prominently, modern general-purpose CPUs …

The presence of control-flow divergence in loops can either hinder or impede auto-
vectorization as a compiler transformation to exploit parallelism enabled by Single …

Abstract Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. SIMD model is …

Abstract (DE) Spaltenorientierte InMemory Datenbanksysteme müssen sowohl Basisdaten
als auch generierte Zwischenergebnisse während der Anfrageverarbeitung im …

Abstract (DE) Kontinuierlich wachsende Mengen an zu verwaltenden Daten und komplexer
werdende analytische Anfragen erfordern eine stetige Weiterentwicklung und Verbesserung …