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Parallelizing loops in database programming languages

机译:在数据库编程语言中并行化循环

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Database programming languages (DBPLs), fourth generation languages (4GLs) and embedded SQL all include the ability to iterate sequentially through a set/relation. Nested iterators can be used to express joins. Without program analysis, such joins must be evaluated using a tuple-at-a-time join algorithm at a central site, otherwise program semantics may be violated. This paper's analysis often allows parallel join algorithms to be used. Also, this paper's compile-time optimizations can produce better parallel code than a straightforward parallelization of the nested iterators. The transformations allow the compiler to identify parallelization opportunities that it could not detect in the original code. These techniques are important for aiding the migration from hand-optimized code on a sequential machine to system-optimized code on a parallel machine. Without such rewrites, moving to a parallel system may produce only meager performance improvements when porting legacy systems.
机译:数据库编程语言(DBPLS),第四代语言(4GLS)和嵌入式SQL都包括顺序通过集/关系顺序迭代的能力。嵌套迭代器可用于表达联合。如果没有程序分析,必须使用在中央站点的元组 - AT-A-time加入算法进行评估这样的连接,否则可能会违反节目语义。本文的分析通常允许使用并行连接算法。此外,本文的编译时间优化可以产生比嵌套迭代器的直接并行化更好的并行代码。转换允许编译器识别它无法在原始代码中检测到的并行化机会。这些技术对于在顺序计算机上的手动优化代码中迁移到并行计算机上的系统优化代码很重要。在没有这样的重写的情况下,移动到并行系统可能仅在移植传统系统时产生微薄性能改进。

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