Shared Cache Organization for Multiple-Stream Computer Systems.

Abstract

Organizations of shared two-level memory hierarchies for parallel-pipelined multiple instruction stream processors are studied. The multicopy of data problems are totally eliminated by sharing the caches. All memory modules are assumed to be identical and cache addresses are interleaved by sets. For a parallel-pipelined processor of order (s,p), which consists of p parallel processors each of which is a pipelined processor with degree of multiprogramming, s, there can be up to sp cache requests from distinct instruction streams in each instruction cycle. The cache memory interference and shared cache hit ratio in such systems are investigated. The study shows that the set associative mapping mechanism, the write through with buffering updating scheme and the no write allocation bloc fetch strategy are suitable for shared cache systems. However, for private cache systems, the write back with buffering updating scheme and the write allocation block fetch strategy are considered in this thesis. Performance analysis is carried out by using discrete Markov Chain and probability based theorems. Some design tradeoffs are discussed and examples are given to illustrate a wide variety of design options that can be obtained. Performance differences due to alternative architectures are also shown by a performance comparison between shared cache and private cache for a wide range of parameters.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1981
Accession Number
ADA124387

Entities

People

  • Chi-chung Yeh

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computer Programming
  • Computer Programs
  • Computers
  • Content Addressable Memory
  • Electrical Engineering
  • Logic Gates
  • Markov Chains
  • Markov Models
  • Memory Devices
  • Multiple Access
  • Multiprogramming
  • Parallel Processors
  • Plastic Explosives
  • Probabilistic Models
  • Probability
  • Semiconductors
  • Two Dimensional

Readers

  • Parallel and Distributed Computing.