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Communication Dans Un Congrès Année : 2014

Exploring the vectorization of Python constructs using Pythran and Boost SIMD

Résumé

The Python language is highly dynamic, most notably due to late binding. As a consequence, programs using Python typically run an order of magnitude slower than their C counterpart. It is also a high level language whose semantic can be made more static without much change from a user point of view in the case of mathematical applications. In that case, the language provides several vectorization opportunities that are studied in this paper, and evaluated in the context of Pythran, an ahead-of-time compiler that turns Python module into C++ meta-programs
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Dates et versions

hal-00981551 , version 1 (22-04-2014)

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Serge Guelton, Joel Falcou, Pierrick Brunet. Exploring the vectorization of Python constructs using Pythran and Boost SIMD. WPMVP 2014 : Workshop on Programming models for SIMD/Vector processing, Feb 2014, Orlando, United States. pp.79-86, ⟨10.1145/2568058.2568060⟩. ⟨hal-00981551⟩
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