# State-of-the-Art on Query & Transaction Processing Acceleration

## TL;DR

This paper reviews the use of GPUs for accelerating query and transaction processing in database systems, highlighting key properties, challenges, and future research directions for GPU-accelerated databases.

## Contribution

It provides a comprehensive overview of GPU-accelerated database architectures, identifying open challenges and research areas for future development.

## Key findings

- GPU architectures offer significant potential for data processing acceleration.
- Key challenges include data transfer bottlenecks and architecture design complexities.
- Open research areas involve optimizing GPU integration in database systems.

## Abstract

The vast amount of processing power and memory bandwidth provided by modern Graphics Processing Units (GPUs) make them a platform for data-intensive applications. The database community identified GPUs as effective co-processors for data processing. In the past years, there were many approaches to make use of GPUs at different levels of a database system. In this Internal Technical Report, based on the [1] and some other research papers, we identify possible research areas at LIP6 for GPU-accelerated database management systems. We describe some key properties, typical challenges of GPU-aware database architectures, and identify major open challenges.