Experiments with list ranking for explicit multi-threaded (XMT) instruction parallelism

  • Authors:
  • Dascal Vishkin;Uzi Vishkin

  • Affiliations:
  • Univ. of Maryland, College Park;Univ. of Maryland, College Park

  • Venue:
  • Journal of Experimental Algorithmics (JEA)
  • Year:
  • 2000

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Abstract

Algorithms for the problem of list ranking are empiricallystudied with respect to the Explicit Multi-Threaded (XMT) platformfor instruction-level parallelism (ILP). The main goal of thisstudy is to understand the differences between XMT and moretraditional parallel computing implementation platforms/models asthey pertain to the well studied list ranking problem. The main twofindings are: (i) good speedups for much smaller inputs arepossible and (ii) in part, the first finding is based on a newvariant of a 1984 algorithm, called the No-Cut algorithm. The paperincorporates analytic (non-asymptotic) performance analysis intoexperimental performance analysis for relatively small inputs. Thisprovides an interesting example where experimental research andtheoretical analysis complement one another. ExplicitMulti-Threading (XMT) is a fine-grained computation frameworkintroduced in our SPAA'98 paper. Building on some key ideas ofparallel computing, XMT covers the spectrum from algorithms througharchitecture to implementation; the main implementation relatedinnovation in XMT was through the incorporation of low-overheadhardware and software mechanisms (for more effective fine-grainedparallelism). The reader is referred to that paper for detail onthese mechanisms. The XMT platform aims at faster single-taskcompletion time by way of ILP.