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cs.DB2026

FliX: Flipped-Indexing for Scalable GPU Queries and Updates

Rosina Kharal, Trevor Brown, Justus Henneberg +1

GPU-based concurrent data structures (CDSs) achieve high throughput for read-only queries, but efficient support for dynamic updates on fully GPU-resident data remains challenging.…

cs.DB2026

GPU-RMQ: Accelerating Range Minimum Queries on Modern GPUs

Lara Kreis, Justus Henneberg, Valentin Henkys +2

Range minimum queries are frequently used in string processing and database applications including biological sequence analysis, document retrieval, and web search. Hence, various…

cs.DB2025

Bigger Is Not Better: The Fastest Static GPU Index Is Also Lightweight!

Justus Henneberg, Felix Schuhknecht

Sorting and binary searching a dense array can be considered the simplest and most space efficient form of indexing. This holds especially on GPUs as they exhibit exceptional sorti…

cs.DB2024

More Bang For Your Buck(et): Fast and Space-efficient Hardware-accelerated Coarse-granular Indexing on GPUs

Justus Henneberg, Felix Schuhknecht, Rosina Kharal +1

In recent work, we have shown that NVIDIA's raytracing cores on RTX video cards can be exploited to realize hardware-accelerated lookups for GPU-resident database indexes. On a hig…

cs.DB2023

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

Justus Henneberg, Felix Schuhknecht

Data management on GPUs has become increasingly relevant due to a tremendous rise in processing power and available GPU memory. Similar to main-memory systems, there is a need for…

cs.DB2021

Northlight: Declarative and Optimized Analysis of Atmospheric Datasets in SparkSQL

Justus Henneberg, Felix Schuhknecht, Philipp Reutter +2

Performing data-intensive analytics is an essential part of modern Earth science. As such, research in atmospheric physics and meteorology frequently requires the processing of ver…