A Framework for Enhancing Data Reuse via Associative Reordering

Authors

Kevin Stock, The Ohio State University
Martin Kong, The Ohio State University
Tobias Grosser, École Normale Supérieure
Louis Noë Pouchet, University of California, Los Angeles
Fabrice Rastello, Institut National de Recherche en Informatique
J. Ramanujam, LOUISIANA, STATE OF
P. Sadayappan, The Ohio State University

Document Type

Conference Proceeding

Publication Date

6-5-2014

Abstract

The freedom to reorder computations involving associative operators has been widely recognized and exploited in designing parallel algorithms and to a more limited extent in optimizing compilers.

Publication Source (Journal or Book title)

ACM SIGPLAN Notices

First Page

65

Last Page

76

Recommended Citation

Stock, K., Kong, M., Grosser, T., Pouchet, L., Rastello, F., Ramanujam, J., & Sadayappan, P. (2014). A Framework for Enhancing Data Reuse via Associative Reordering. ACM SIGPLAN Notices, 49 (6), 65-76. https://doi.org/10.1145/2594291.2594342