By Topic

Automatic data structure selection and transformation for sparse matrix computations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Bik, A.J.C. ; Dept. of Comput. Sci., Leiden Univ., Netherlands ; Wijshoff, Harry A.G.

The problem of compiler optimization of sparse codes is well known and no satisfactory solutions have been found yet. One of the major obstacles is formed by the fact that sparse programs explicitly deal with particular data structures selected for storing sparse matrices. This explicit data structure handling obscures the functionality of a code to such a degree that optimization of the code is prohibited, for instance, by the introduction of indirect addressing. The method presented in this paper delays data structure selection until the compile phase, thereby allowing the compiler to combine code optimization with explicit data structure selection. This method enables the compiler to generate efficient code for sparse computations. Moreover, the task of the programmer is greatly reduced in complexity

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:7 ,  Issue: 2 )