High Performance Computing - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Artificial Intelligence -- Parallel and Distributed Processing for Unsupervised Patient Phenotype Representation -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 4 Experiments and Results -- 5 Conclusions -- References -- Evolutionary Algorithms for Convolutional Neural Network Visualisation -- 1 Introduction -- 2 Convolutional Neural Networks -- 2.1 What Is a Convolutional Neural Network? -- 2.2 The Understanding/Visualisation Issue -- 3 Evolutionary Algorithms -- 3.1 An EA Example -- 3.2 Differences and Similarities Between EA and NN -- 4 Our Approach: Strategy and Implementation -- 4.1 The Initial Strategy -- 4.2 Our EA -- 4.3 Running the EA -- 5 Results and Discussion -- 6 Conclusion and Future Works -- References -- Breast Cancer Classification: A Deep Learning Approach for Digital Pathology -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Dataset Creation -- 2.4 CNN Architecture -- 2.5 Methods -- 3 Results -- 4 Conclusions -- References -- Where Do HPC and Cognitive Science Meet in Latin America? -- 1 Introduction -- 2 Artificial Intelligence and Cognitive Science -- 2.1 Origins and Fundamental Goals of Artificial Intelligence -- 2.2 Cognitive Science: Goals and Disciplines -- 2.3 The Standard Fields of Cognitive Science -- 2.4 The Cognitive Science Research Framework -- 3 HPC and AI Meet -- 4 The Need for a Closer HPC-CogSci Relationship -- 4.1 Trends in Cognitive Science -- 4.2 A Research Example: Modeling Recall in Human Memory -- 5 How to Bring HPC and Cognitive Science Closer in Latin America -- 6 Conclusions -- References -- Accelerators -- A Hybrid Reinforcement Learning and Cellular Automata Model for Crowd Simulation on the GPU -- 1 Introduction -- 2 Related Work -- 2.1 Reinforcement Learning in Crowd Simulation

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