A Block-Based Mode Selection Model for SIMD/SPMD Parallel Environments |
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| Affiliation: | 1. Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK;2. Institute of Neurology, UCL, London WC1N 3BG, UK;3. Wellcome Centre for Human Neuroimaging, UCL, London WC1N 3AR, UK;4. Institute of Cognitive Neuroscience, UCL, London WC1N 3AZ, UK;5. School of Biological and Chemical Sciences, QMUL, London E1 4NS, UK;6. Sainsbury Wellcome Centre for Neural Circuits and Behaviour, UCL, London W1T 4JG, UK;7. Research department of Cell and Developmental Biology, UCL, London WC1E 6BT, UK;1. Departamento de Biologia Vegetal, Instituto de Biologia, CP 6109, Universidade Estadual de Campinas, CEP 13083-970, Campinas, SP, Brazil;2. Embrapa Soja, Rodovia Carlos João Strass, s/n°, Acesso Orlando Amaral, Distrito de Warta, CP 231, CEP 86001-970, Londrina, PR, Brazil;3. Centro de Tecnologia Canavieira (CTC), Rua Santo Antônio, Centro, CEP 13400-160, Piracicaba, SP, Brazil;4. Centro de Biologia Molecular and Engenharia Genética, Universidade Estadual de Campinas, CEP 13083-875, Campinas, SP, Brazil;5. Centro de Cana, Instituto Agronômico de Campinas, CEP 14001-970, Ribeirão Preto, SP, Brazil |
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| Abstract: | One of the challenges for parallel compilers and compiler-related tools is, given a machine-independent parallel language, to generate executable code for a variety of computational models, and to identify those specific parallel modes for which a program is well-suited. One portion of this problem, developing a method for estimating the relative execution time of a data-parallel algorithm in an environment capable of the SIMD and SPMD (MIMD) modes of parallelism, is presented. Given a data-parallel program in a language whose syntax is mode-independent and empirical information about instruction execution time characteristics, the goal is to use static source-code analysis to determine an implementation that results in an optimal execution time for a mixed-mode machine capable of SIMD and SPMD parallelism. Statistical information about individual operation execution times and paths of execution through a parallel program is assumed. A secondary goal of this study is to indicate language, algorithm, and machine characteristics that must be researched to learn how to provide the information needed to obtain an optimal assignment of parallel modes to program segments. |
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