Query Compilation for the Heterogeneous Many Core Age

现代处理器的性能主要受固定能源预算的约束。这道电源墙迫使处理器供应商将他们的处理器专门用于某些应用，以提供用户期望的加速比。这种专门化导致了异类处理器的格局，其中每个处理器都有独特的属性和功能。将数据库系统优化到具有不同体系结构的处理器是一项非常昂贵的任务，因为数据库操作员需要由专业程序员为每个新的处理器重新实现和优化。拟议的项目的目标是开发一些概念，使数据库系统能够自动适应这种以前未知的异类处理器，从而避免手动逐个处理器进行调整。该项目的核心思想是向数据库操作符引入各种变化(例如，代码优化、数据结构和并行化策略)，这允许我们生成数据库操作符的每个处理器的定制实现。由于这种变体生成创建了很大的搜索空间，我们将研究查询优化器的概念，该优化器可以自动为每个处理器选择高效的运算符实现，而不需要事先了解所使用的处理器。

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.