用VHDL研究寄存器/文件/缓存微体系结构

MICRO 24 Pub Date : 1991-09-01 DOI:10.1145/123465.123510
Samarina Makhdoom, D. Tabak, R. Auletta
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引用次数: 0

摘要

在risc型微处理器中,利用VHDL建模研究了CPU寄存器文件大小与片上缓存大小的比较对处理器性能的影响。选择英特尔80860(或i860)作为本研究的模型。使用Linpack基准测试作为生成性能估计的示例。采用VHDL对i860微结构进行了建模和仿真。在修改浮点寄存器文件的大小(实际大小:32位寄存器或16位寄存器)时,测试了i860执行Linpack基准测试的性能。在Sun-3工作站上使用Intermetrics 3.0 VHDL工具集对模型进行了编译和仿真。在研究过程中,提出了一种称为通用模型的指令分类方案。它允许通过分配指令及其相关属性对应用程序进行建模来快速描述应用程序,而无需完全指定相应的代码或目标处理器体系结构。结果清楚地表明,当寄存器文件大小增加一倍时,在执行所选基准测试时,性能显著提高。进一步增加寄存器文件大小会导致性能的适度提高。该研究还表明,为了通过仅增加缓存大小来实现相同的性能改进,必须将缓存增加一个数量级以上,这大大超过了当前VLSI技术的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Register/ file/ cache microarchitecture study using VHDL
The influence on the processor performance comparing the CPU register file size to on-chip cache size, in a RISC-type microprocessor is investigated using VHDL modeling. The Intel 80860(or i860) was selected as a model for this study. The Linpack benchmark was used as an example for generating performance estimates. The i860 micmarchitecture was modeled and simulated using VHDL., The i860 performance executing the Linpack benchmark was tested while modifying the size of its floating point register file (actual size: 32 32-bit, or 16 64-bit registers). The model was compiled and simulated using the Intermetrics version 3.0 VHDL toolset on a Sun-3 workstation. An instruction classification scheme, called the generic model, was developed in the course of this study. It allows rapid characterization of applications by modeling them by the distribution of instructions and their relevant properties without the need to fully specify the corresponding code or target processor architecture. The results clearly indicate a signitlcant increase in performance while executing the selected benchmark when the register file size is doubled. Further increases in the register file size result in modest increases in performance. The study also shows that in order to achieve the same performance improvement by increasing only the cache size one would have to increase the cache by more than an order of magnitude, considerably exceeding current limitations of VLSI technology.
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