Load-Aware Inter-Co-Processor Parallelism in Database Query ProcessingI

For a decade, the database community has been exploring graphics process-ing units and other co-processors to accelerate query processing. While the developed algorithms often outperform their CPU counterparts, it is not ben-eficial to keep processing devices idle while over utilizing others. Therefore, an approach is needed that efficiently distributes a workload on available (co-)processors while providing accurate performance estimates for the query optimizer. In this paper, we contribute heuristics that optimize query pro-cessing for response time and throughput simultaneously via inter-device parallelism. Our empirical evaluation reveals that the new approach achieves speedups up to 1.85 compared to state-of-the-art approaches while preserving accurate performance estimations. In a further series of experiments, we eval-uate our approach on two new use cases: joining and sorting. Furthermore, we use a simulation to assess the performance of our approach for systems with multiple co-processors and derive some general rules that impact performance in those systems