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Performance Analysis And Fitness Of Gpgpu And Multicore Architectures For Scientific Applications, Mohammad Bhuiyan

All Dissertations

Recent trends in computing architecture development have focused on exploiting task- and data-level parallelism from applications. Major hardware vendors are experimenting with novel parallel architectures, such as the Many Integrated Core (MIC) from Intel that integrates 50 or more x86 processors on a single chip, the Accelerated Processing Unit from AMD that integrates a multicore x86 processor with a graphical processing unit (GPU), and many other initiatives from other hardware vendors that are underway.
Therefore, various types of architectures are available to developers for accelerating an application. A performance model that predicts the suitability of the architecture for accelerating an …

Towards An Information Theoretic Framework For Evolutionary Learning, Stuart William Card

Electrical Engineering and Computer Science - Dissertations

The vital essence of evolutionary learning consists of information flows between the environment and the entities differentially surviving and reproducing therein. Gain or loss of information in individuals and populations due to evolutionary steps should be considered in evolutionary algorithm theory and practice. Information theory has rarely been applied to evolutionary computation - a lacuna that this dissertation addresses, with an emphasis on objectively and explicitly evaluating the ensemble models implicit in evolutionary learning. Information theoretic functionals can provide objective, justifiable, general, computable, commensurate measures of fitness and diversity.

We identify information transmission channels implicit in evolutionary learning. We define …