collaborators

5 papers

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.DB2026

The Case for Multi-Version Experimental Evaluation (MVEE)

Simon Jörz, Felix Schuhknecht

In the database community, we typically evaluate new methods based on experimental results, which we produce by integrating the proposed method along with a set of baselines in a s…

cs.DB2026

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.DB2025

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…