loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Second International Symposium on Parallel and Distributed Computing
Data Dependence Analysis for Intra-Register Vectorization
Ljubljana, Slovenia
October 13-October 14
ISBN: 0-7695-2069-3
Patricio Bulic, University of Ljubljana, Slovenia
Veselko Gustin, University of Ljubljana, Slovenia
There are a number of data dependence tests that have been proposed in the literature. In each test there is a different trade-off between accuracy and efficiency. The most widely used approximate data dependence tests are the Banerjee inequality and the GCD test; whereas the Omega test is a well-known exact data dependence test.
In this paper we present a new, fast data dependence test for array references with linear subscripts, which is used in a vectorizing compiler for microprocessors with a multimedia extension. Our test is suitable for use in a dependence analyser that is organized is as a series of tests, progressively increasing in accuracy, as a replacement for the GCD or Banerjee tests.
Citation:
Patricio Bulic, Veselko Gustin, "Data Dependence Analysis for Intra-Register Vectorization," ispdc, pp.50, Second International Symposium on Parallel and Distributed Computing, 2003
Usage of this product signifies your acceptance of the Terms of Use.