Traditional database systems execute database queries on disk-based tables. Research has shown that traditional disk-based database query execution often suffers from high penalties arising from for example, memory latencies, processors waiting for data to be fetched from the memory, and L1 data and L2 instruction stalls. Therefore, to tackle this problem, multiprocessors are being increasingly utilized for executing database queries. Complementary to the disk-based tables are the in-memory tables. In-memory tables are faster than disk-based tables because the fetching from and loading to the disk component is eliminated. In-memory enabled systems can therefore use more efficient techniques to provide maximum performance.
A Graphics Processing Unit (GPU) is a massively parallel piece of hardware which can be thought of as several processors with its own local memory. A GPU may operate as an independent co-processor within the host computer. Back in the late nineties, the games industry provided the necessary impetus for the development of the GPU for accelerating graphics in games. Recently, architectures have been configured to support programmability. That is, general-purpose programs may be written to run on the GPU. GPU enabled programs are well suited to problems that involve data-parallel computations where the same program is executed on different data with high arithmetic intensity.
As such, GPU enabled database systems are presented herein.