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PPKE ITK PhD and MPhil Thesis Classes

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Contents<br />

1 Introduction 1<br />

1.1 Cellular Neural/Nonlinear Network . . . . . . . . . . . . . . . . . 4<br />

1.1.1 Linear templates . . . . . . . . . . . . . . . . . . . . . . . 4<br />

1.1.2 Nonlinear templates . . . . . . . . . . . . . . . . . . . . . 6<br />

1.2 Cellular Neural/Nonlinear Network - Universal Machine . . . . . . 7<br />

1.3 CNN-UM Implementations . . . . . . . . . . . . . . . . . . . . . . 9<br />

1.4 Field Programmable Gate Arrays . . . . . . . . . . . . . . . . . . 12<br />

1.4.1 The general structure of FPGAs . . . . . . . . . . . . . . . 12<br />

1.4.2 Routing Interconnect . . . . . . . . . . . . . . . . . . . . . 14<br />

1.4.3 Dedicated elements, heterogenous structure . . . . . . . . 20<br />

1.4.4 Xilinx FPGAs . . . . . . . . . . . . . . . . . . . . . . . . . 22<br />

1.4.4.1 Xilinx Virtex 2 FPGA . . . . . . . . . . . . . . . 22<br />

1.4.4.2 Xilinx Virtex 5 FPGAs . . . . . . . . . . . . . . 23<br />

1.4.4.3 The capabilities of the modern Xilinx FPGAs . . 24<br />

1.5 IBM Cell Broadb<strong>and</strong> Engine Architecture . . . . . . . . . . . . . 26<br />

1.5.1 Cell Processor Chip . . . . . . . . . . . . . . . . . . . . . . 26<br />

1.5.2 Cell Blade Systems . . . . . . . . . . . . . . . . . . . . . . 32<br />

1.6 Recent Trends in Many-core Architectures . . . . . . . . . . . . . 34<br />

2 Mapping the Numerical Simulations of Partial Differential Equations<br />

35<br />

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35<br />

2.1.1 How to map CNN array to Cell processor array? . . . . . . 36<br />

2.1.1.1 Linear Dynamics . . . . . . . . . . . . . . . . . . 36<br />

2.1.1.2 Nonlinear Dynamics . . . . . . . . . . . . . . . . 45<br />

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