Boosting Open-Source Database Engines with Graphics Processors

In recent years, graphics chips known as GPUs have become increasingly important in the field of supercomputing. These chips are effective on heavy and highly parallelizable calculations. They naturally found applications in the scientific world for example in weather forecasting, molecular modeling and audio or video processing.
Previous work has shown the ability to implement on a GPU some of the operations that can typically be found in database engines. in this context, we studied how to adapt an open source relational database engine to allow it to run on a GPU. for this, we developed a prototype based on the SQLite open source project allowing us to perform a variety of insertion and selection queries that manipulate data stored in the GPU memory.
Our database engine support record filtering, relational joins, aggregation functions and most of the operators and functions working on both numbers and strings. for all of those, we implemented efficient algorithms taking into account the specific architecture of the GPU. the execution speedups of most queries were improved by a factor from ten to two hundred in comparison of the CPU counterpart. Therefore, our GPU-running database engine is able to improve system responsiveness and/or reduce the number of machines needed for an equivalent amount of data to process, thereby improving the energy efficiency.