DocumentCode :
3472118
Title :
Multi-platform auto-vectorization
Author :
Nuzman, Dorit ; Henderson, Richard
Author_Institution :
IBM Haifa Res. Lab, Israel
fYear :
2006
fDate :
26-29 March 2006
Abstract :
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 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 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.
Keywords :
parallel processing; program compilers; SIMD architecture; SIMD model; automatic vectorizer; multiplatform auto-vectorization; multitargetable compiler; single instruction multiple data; Computer aided instruction; Computer architecture; Costs; Digital signal processing; Ecosystems; Kernel; Linux; Optimizing compilers; Parallel processing; Registers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Code Generation and Optimization, 2006. CGO 2006. International Symposium on
Print_ISBN :
0-7695-2499-0
Type :
conf
DOI :
10.1109/CGO.2006.25
Filename :
1611548
Link To Document :
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