Query Compilation for the Heterogeneous Many Core Age

点击翻译按钮获取中文摘要

The performance of modern processors is primarily bound by a fixed energy budget. This power wall forces processor vendors to specialize their processors to certain applications to provide the speedups users expect. This specialization leads to a landscape of heterogeneous processors, where each processor has unique properties and capabilities. Optimizing database systems to processors with different architectures is a very costly task, because database operators need to be re-implemented and optimized for each new processor by expert programmers. The proposed project has the goal to develop concepts that allow database systems to adapt themselves automatically to such heterogeneous, previously unknown processors, which avoids manual per-processor tuning. The core idea of the project is to introduce variations to database operators (e.g., code optimizations, data structures and parallelization strategies), which allows us to generate custom per-processor implementations of database operators. As this variant generation creates a large search space, we will research concepts for a query optimizer that can select efficient implementations of an operator for each processor automatically without prior knowledge of the processors used.