The recent proliferation of the Single Instruction Multiple Data (SIMD) model has lead to a wide variety of implementations. These have been incorporated into many platforms, from gaming machines and embedded DSPs to general purpose architectures. In this paper we present an automatic vectorizer as implemented in GCC - the most multi-targetable compiler available today. We discuss the considerations that are involved in developing a multi-platform vectorization technology, and demonstrate how our vectorization scheme is suited to a variety of SIMD architectures. Experiments on four different SIMD platforms demonstrate that our automatic vectorization scheme is able to efficiently support individual platforms, achieving significant speedups on key kernels.
By: Dorit Naishlos; Richard Henderson
Published in: H-0236 in 2005
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to reports@us.ibm.com .