Vectorized data processing on the cell broadband engine
Vectorized data processing on the cell broadband engine
复制标题
细胞宽带引擎上的矢量化数据处理
DOI：
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发表时间：
2007
期刊：
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通讯作者：
P. Boncz
中科院分区：
文献类型：
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作者：
S. Héman;N. Nes;M. Zukowski;P. Boncz
在这项工作中，我们研究了细胞宽带引擎的数据库处理的适用性。我们首先概述了Cell的主要架构特征，并使用微基准测试来表征其内存基础设施的延迟和吞吐量。然后，我们讨论了将RDBMS软件移植到Cell的挑战：（i）所有计算都需要SIMD化，（ii）所有性能关键分支都需要消除，（iii）程序代码大小的非常小的硬限制应该得到尊重。
虽然我们认为传统的数据库实现，即具有Volcano风格元组流水线的行存储，很难适合Cell，但事实证明，在使用列式处理的数据库中，这三个挑战很容易满足。我们通过在PowerPC上运行操作符管道，在Cell上实现了MonetDB/X100的向量化查询处理模型的概念验证端口，但让它在其SPE核心上执行向量化原语（数据并行）。对TPC-H Q1的性能评估表明，Cell上的向量化查询处理可以超过传统的PowerPC和Itanium 2 CPU 20倍。
In this work, we research the suitability of the Cell Broadband Engine for database processing. We start by outlining the main architectural features of Cell and use micro-benchmarks to characterize the latency and throughput of its memory infrastructure. Then, we discuss the challenges of porting RDBMS software to Cell: (i) all computations need to SIMD-ized, (ii) all performance-critical branches need to be eliminated, (iii) a very small and hard limit on program code size should be respected.
While we argue that conventional database implementations, i.e. row-stores with Volcano-style tuple pipelining, are a hard fit to Cell, it turns out that the three challenges are quite easily met in databases that use column-wise processing. We managed to implement a proof-of-concept port of the vectorized query processing model of MonetDB/X100 on Cell by running the operator pipeline on the PowerPC, but having it execute the vectorized primitives (data parallel) on its SPE cores. A performance evaluation on TPC-H Q1 shows that vectorized query processing on Cell can beat conventional PowerPC and Itanium2 CPUs by a factor 20.