New Architectures for New Applications: PIM NUMAs for Commercial Workloads

这项工作的目标是使高回报的技术，高端并行计算的数据库应用程序。这项工作涉及探索下一代分布式共享内存（DSM）架构上运行高性能的内存驻留并行数据库。该架构提出了一个全新的节点和系统组织的基础上处理器在内存（PIM）芯片技术。它包括用于数据库的智能内存、对可重新配置性的支持以及对查询的推测性执行的硬件支持。本研究还探讨了这种体系结构，新的算法来并行化数据库查询，布局和映射数据库数据和代码，并调度数据库线程。这些算法也利用了一些硬件支持，它们被设计为具有缓存意识，因此利用了深层内存层次结构。算法的一个子集将在一个真实的并行化编译器（Polaris）中实现，并在一个真实的并行数据库上进行测试，该数据库将被重写以实现可扩展性（Postgres95）。重写的Postgres95代码将提供给其他学术研究人员使用。

The objective of this work is to enable high pay-off technologies for high-end parallel computing of database applications. The work involves exploring the next-generation distributed shared-memory (DSM) architectures on which to run high-performance memory-resident parallel databases. The architecture proposed has a radically new node and system organization based on processor-in-memory (PIM) chip technology. It includes intelligent memory for databases, support for reconfigurability and hardware support for speculative execution of queries. This research also explores, for this architecture, novel algorithms to parallelize database queries, lay out and map database data and code, and schedule database threads. These algorithms, which also exploit some hardware support, are designed to be cache-conscious and, therefore, exploit deep memory hierarchies. A subset of the algorithms are to be implemented in a real parallelizing compiler (Polaris) and tested on a real parallel database that will be rewritten for scalability (Postgres95). The rewritten Postgres95 code will be made available to other academic researchers for their use.