III: Small: Extending and Automating Dynamic Specialization of Database Management Systems

数据库管理系统（dbms）在工业中无处不在，其性能和功能在商业IT基础设施中至关重要。在改进这些关键系统的性能方面已经做了很多工作。该项目采用了一种互补的正交方法来大幅提高dbms的性能。这是通过利用有关DBMS的运行时信息来动态地专门化DBMS代码来实现的，以便尽可能多地消除不必要的工作。这种动态代码优化，我们称之为“微专门化”，是非常积极的，并且远远超出了使用现有编译器优化技术所能达到的效果。这种对运行时代码优化的关注也与当前大多数关于DBMS性能改进的研究有很大的不同。该项目研究了自动识别代码序列的算法，其中微专门化可以有效地应用；微专门化识别目标代码序列的算法；以及确保结果代码正确性的技术。对不同DBMS的初步研究表明，当应用于成熟的高性能DBMS和行业标准基准时，微专门化提供了显著的性能改进，并且在对DBMS体系结构影响最小的情况下，有很多机会获得其他实质性的性能提升。这个项目更广泛的影响包括提高各种公司使用的IT基础设施的效率，从而提高整体生产力。研究生和本科生参与研究活动的各个方面，作为项目的组成部分。在将研究活动纳入本科课程和让本科生（包括妇女和代表性不足的少数民族成员）参与研究方面，pi有着良好的记录；这个项目延续了这个传统。欲了解更多信息，请访问网站http://www.cs.arizona.edu/projects/microspecialization/。

Database management systems (DBMSs) are ubiquitous in industry and their performance and functionality are crucially important in commercial IT infrastructure. There has been a lot of work on improving the performance of these critical systems. This project adopts a complementary and orthogonal approach to substantially increasing the performance of DBMSs. This is done by exploiting runtime information about the DBMS to specialize the DBMS code on the fly in order to eliminate as much unnecessary work as possible. This dynamic code optimization, which we term "micro-specialization", is highly aggressive and goes well beyond what can be achieved using existing compiler optimization technology. This focus on runtime code optimization is also very different from most of the current research on DBMS performance improvement. The project investigates algorithms for automatic identification of code sequences where micro-specialization may profitably be applied; algorithms that can micro-specialize such identified target code sequences; and techniques for ensuring the correctness of the resulting code. Preliminary studies on disparate DBMSes suggest that micro-specialization offers significant performance improvements when applied to mature, high-performance DBMSs and to industry-standard benchmarks, and that there are rich opportunities for other substantial performance gains, with minimal impact on the DBMS architecture.Broader impacts of this project include increased efficiency of the IT infrastructure used by a wide variety of companies, leading to improved overall productivity. Graduate and undergraduate students are involved in all aspects of the research activities as an integral part of the project. The PIs have an established track record of integrating research activities into the undergraduate curriculum and involving undergraduates, including women and members of underrepresented minorities, in research; this project continues this tradition.For further information see the web site at http://www.cs.arizona.edu/projects/microspecialization/ .