doppioDB: A hardware accelerated database
doppioDB: A hardware accelerated database
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doppioDB：硬件加速数据库
DOI：
10.1145/3035918.3058746
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
G. Alonso
中科院分区：
文献类型：
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作者：
David Sidler;Muhsen Owaida;Z. István;Kaan Kara;G. Alonso
关系数据库为广泛的应用程序提供了丰富的功能。然而，有些任务它们不是最佳的，例如当处理变得更复杂时（例如，正则表达式求值、数据分析）或者数据结构化程度较低（例如，文本或长字符串）。随着存储在关系数据库中的用户生成数据量的增加，对非结构化文本数据的分析需求也越来越大。与此同时，需要更复杂的分析运算符从大量收集的数据中提取有用的信息。然而，许多分析运算符会导致大量的计算复杂性，不适合多个查询共享可用资源的数据库引擎。在这个演示中，我们将展示使用专用硬件执行此类任务的好处，并强调使用基于硬件的操作符扩展数据库引擎的灵活、可重用机制的重要性。我们的混合数据库引擎doppioDB部署在新兴的Xeon+FPGA多核架构上，其中CPU和FPGA可以对同一内存进行缓存一致性访问，因此硬件操作员可以直接访问数据库表。该演示展示了硬件操作员的加速优势，以及doppioDB在适应不断变化的工作负载方面的灵活性。
Relational databases provide a wealth of functionality to a wide range of applications. Yet, there are tasks for which they are less than optimal, for instance when processing becomes more complex (e.g., regular expression evaluation, data analytics) or the data is less structured (e.g., text or long strings). With the increasing amount of user-generated data stored in relational databases, there is a growing need to analyze unstructured text data. At the same time more complex analytical operators are required to extract useful information from the vast amount of collected data. However, many analytical operators incur a significant compute complexity not suitable to database engines where multiple queries share the available resources. In this demonstration we show the benefit of using specialized hardware for such tasks and highlight the importance of a flexible, reusable mechanism for extending database engines with hardware-based operators. Our hybrid database engine, doppioDB, is deployed on an emerging Xeon+FPGA multicore architecture where the CPU and FPGA have cache-coherent access to the same memory, such that the hardware operators can directly access the database tables. The demonstration is illustrating the acceleration benefits of hardware operators, as well as doppioDB's flexibility in accommodating changing workloads.