R2m:可重构重写机

IF 0.5 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Parallel Processing Letters Pub Date : 1994-06-01 DOI:10.1142/S0129626494000181
R. Ramesh
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引用次数: 1

摘要

术语重写是一种流行的符号计算范式,如公式操作、定理证明和非过程编程语言的实现。在重写过程中,要求最高的操作是根据重写规则对术语进行模式匹配,从而重复简化术语。我们描述了一个并行架构R2M来加速这个操作。R2M既可以使用自己的内存作为独立处理器运行,也可以使用主机的主内存作为连接到主机的后端设备运行。R2M只使用固定数量(与输入大小无关)的处理单元和固定容量的辅助内存单元,但是它能够处理在简化过程中发生变化的可变大小的重写规则。这可以通过R2M中存在的简单且可重构的互连来实现。最后,R2M使用一种混合方案,该方案结合了使用术语的树表示的并行模式匹配的便利性和效率,以及替换术语的日表示的自然性。
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R2M: A RECONFIGURABLE REWRITE MACHINE
Term rewriting is a popular computational paradigm for symbolic computations such as formula manipulation, theorem proving and implementations of nonprocedural programming languages. In rewriting, the most demanding operation is repeated simplification of terms by pattern matching them against rewrite rules. We describe a parallel architecture, R2M, for accelerating this operation. R2M can operate either as a stand-alone processor using its own memory or as a backend device attached to a host using the host’s main memory. R2M uses only a fixed number (independent of input size) of processing units and fixed capacity auxiliary memory units, yet it is capable of handling variable-size rewrite rules that change during simplification. This is made possible by a simple and reconfigurable interconnection present in R2M. Finally, R2M uses a hybrid scheme that combines the ease, and efficiency of parallel pattern matching using the tree representation of terms, and the naturalness of their dag representation for replacements.
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来源期刊
Parallel Processing Letters
Parallel Processing Letters COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
0.90
自引率
25.00%
发文量
12
期刊介绍: Parallel Processing Letters (PPL) aims to rapidly disseminate results on a worldwide basis in the field of parallel processing in the form of short papers. It fills the need for an information vehicle which can convey recent achievements and further the exchange of scientific information in the field. This journal has a wide scope and topics covered included: - design and analysis of parallel and distributed algorithms - theory of parallel computation - parallel programming languages - parallel programming environments - parallel architectures and VLSI circuits
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