Accelerating Large Table Scan Using Processing-In-Memory Technology

Alexander Baumstark, Muhammad Attahir Jibril, Kai-Uwe Sattler
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Abstract

Abstract Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However, the processing of data from the main memory necessarily has to run via the CPU. This creates a bottleneck, which affects the possible performance of the DBMS. Processing-In-Memory (PIM) is a paradigm to overcome this problem, which was not available in commercial systems for a long time. With the availability of UPMEM, a commercial product is finally available that provides PIM technology in hardware. In this work, we focus on the acceleration of the table scan, a fundamental database query operation. We show and investigate an approach that can be used to optimize this operation by using PIM. We evaluate the PIM scan in terms of parallelism and execution time in benchmarks with different table sizes and compare it to a traditional CPU-based table scan. The result is a PIM table scan that outperforms the CPU-based scan significantly.
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使用内存处理技术加速大表扫描
当今的系统能够在主存中存储大量数据。特别是,内存dbms可以从这种开发中受益。然而,处理来自主存的数据必须通过CPU来运行。这会产生瓶颈,影响DBMS的性能。内存中处理(PIM)是一种克服这个问题的范例,它在很长一段时间内无法在商业系统中使用。随着UPMEM的出现,在硬件中提供PIM技术的商业产品终于出现了。在这项工作中,我们专注于加速表扫描,这是一个基本的数据库查询操作。我们展示并研究了一种可用于通过使用PIM来优化此操作的方法。我们在不同表大小的基准测试中评估PIM扫描的并行性和执行时间,并将其与传统的基于cpu的表扫描进行比较。结果是PIM表扫描的性能明显优于基于cpu的扫描。
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