« Acceleration Method for Non-numerical Processing Using a Vector Merge Function | Main | A Method of Optimization using Production Rules and Local Evaluation Functions and the Macroscopic Behavior during its Computation Processes »

A Method of Vector Processing for Shared Symbolic Data

Kanada, Y., Parallel Computing, Vol. 19, 1993, pp. 1155-1175.

[ Paper PDF file (invalid characters contained)]
[ Paper postscript file ]

Abstract: Conventional processing techniques for pipelined vector processors such as the Cray-XMP, or data-parallel computers, such as the Connection Machines, are generally applied only to independent multiple data prcessing. This paper describes a vector processing method for multiple processings including parallel rewriting of dynamic data strutures with shared elements, and for mutiple procesings that may rewrite the same data item multiple times. This method enables vector processing when entering mutiple data items into a hash table, address calculation sorting, and many other algorithms that handle lists, trees, graphs and other types of symbolic data structures. This method is aplied to several algorithms; consequently, the peformance is improved by a fator of ten on a Hitachi S-810.

[No English abstract is available.]

Introduction to this research theme: Logic/Symbolic Vector Processing

Keywords: Vectorization of symbol processing, Vectorized symbol processing, Parallel symbol processing, Supercomputing, Super symbol processing, Parallel processing, Vector processing

TrackBack

TrackBack URL for this entry:
http://www.kanadas.com/mt/mt-tb.cgi/175

Post a comment

I am looking forward to your comments.

About

This page contains a single entry from the subsite posted on January 1, 1993 12:00 AM.

The previous post in this subsite was Acceleration Method for Non-numerical Processing Using a Vector Merge Function.

The next post in this subsite is A Method of Optimization using Production Rules and Local Evaluation Functions and the Macroscopic Behavior during its Computation Processes.

Many more can be found on the main index page or by looking through the archives.

(C) Copyright 2007 by Yasusi Kanada
Powered by
Movable Type 3.36