0000000001092470
AUTHOR
Justus Henneberg
RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing
Data management on GPUs has become increasingly relevant due to a tremendous rise in processing power and available GPU memory. Just like in the CPU world, there is a need for performant GPU-resident index structures to speed up query processing. Unfortunately, mapping indexes efficiently to the highly parallel and hard-to-program hardware is challenging and often fails to yield the desired performance and flexibility. Therefore, we advocate to take a different route. Instead of proposing yet another hand-tailored index, we investigate whether we can exploit an indexing mechanism that is already built into modern GPUs: The raytracing hardware accelerator provided by NVIDIA RTX cards. To do …
AnyOLAP
The volume of data that is processed and produced by modern data-intensive applications is constantly increasing. Of course, along with the volume, the interest in analyzing and interpreting this data increases as well. As a consequence, more and more DBMSs and processing frameworks are specialized towards the efficient execution of long-running, read-only analytical queries. Unfortunately, to enable analysis, the data first has to be moved from the source application to the analytics tool via a lengthy ETL process, which increases the runtime and complexity of the analysis pipeline. In this work, we advocate to simply skip ETL altogether. With AnyOLAP, we can perform online analysis of dat…