分级存储器的模型

A. Aggarwal, B. Alpern, A. K. Chandra, M. Snir
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引用次数: 265

摘要

本文介绍了计算的层次记忆模型(HMM)。它旨在对内存层次结构中具有多个级别的计算机进行建模。假定访问内存位置x所花费的时间为≤logx²。该模型对搜索、排序、矩阵乘法和FFT的时间复杂度给出了严格的下界和上界。该模型中的高效算法利用了引用的局部性,将数据放入快速内存并在将其返回到较慢的内存之前多次使用它们。结果表明,电路仿真问题本身具有较差的参考局部性。结果扩展到HMM,其中内存访问时间由任意(非递减)函数给定。对于具有多项式存储器访问时间的隐马尔可夫模型,得到了严密的上界和下界;对于任意存储器访问时间,搜索算法、FFT算法和矩阵乘法算法都是最优的。本文还考虑了HMM模型的在线内存管理算法。在内存层次结构的连续“级别”上使用LRU策略的算法被证明是最优的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A model for hierarchical memory
In this paper we introduce the Hierarchical Memory Model (HMM) of computation. It is intended to model computers with multiple levels in the memory hierarchy. Access to memory location x is assumed to take time ⌈ log x ⌉. Tight lower and upper bounds are given in this model for the time complexity of searching, sorting, matrix multiplication and FFT. Efficient algorithms in this model utilize locality of reference by bringing data into fast memory and using them several times before returning them to slower memory. It is shown that the circuit simulation problem has inherently poor locality of reference. The results are extended to HMM's where memory access time is given by an arbitrary (nondecreasing) function. Tight upper and lower bounds are obtained for HMM's with polynomial memory access time; the algorithms for searching, FFT and matrix multiplication are shown to be optimal for arbitrary memory access time. On-line memory management algorithms for the HMM model are also considered. An algorithm that uses LRU policy at the successive “levels” of the memory hierarchy is shown to be optimal.
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