高级合成增强的康涅克斯存储器

Z. Hascsi, B. Mitu, M. Petre, G. Stefan
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引用次数: 1

摘要

符号处理系统的结构缺陷是由于缺乏对其记忆功能的适当实现而产生的。有许多定义良好的内存函数,但是还没有一个适合它们的结构实现。主内存功能通常由软件实现为数据结构,使用RAM作为硬件支持,但在应用程序中性能较低,因为所有实现都依赖于顺序机制。Connex Memory (CM)涉及基本级结构并行性,可以提高树/列表处理的性能。本文研究了一种增强版CM的合成。CM的具体应用包括列表处理、集合操作、字符串匹配和类似prolog的计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-level synthesis of an enhanced Connex memory
Architectural deficiencies in symbolic processing systems are generated by the lack of an appropriate implementation of their memory functions. There are many well-defined memory functions, but there isn't yet an adequate structural implementation for any of them. The main memory functions are usually software implemented as data structures, using RAM as hardware support, but having low performance in applications because all implementations rely on sequential mechanisms. The Connex Memory (CM), involves a base-level structural parallelism that would increase the performance in tree/list processing. This paper is concerned with the synthesis of an enhanced version of CM. Specific applications of the CM include list processing, set operations, string matching and Prolog-like computation.
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