PPKE ITK PhD and MPhil Thesis Classes

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ii CONTENTS 2.1.1.3 Performance comparisons . . . . . . . . . . . . . 48 2.2 Ocean model and its implementation . . . . . . . . . . . . . . . . 49 2.3 Computational Fluid Flow Simulation on Body Fitted Mesh Geometry with IBM Cell Broadband Engine and FPGA Architecture 53 2.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 53 2.3.2 Fluid Flows . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2.3.2.1 Discretization of the governing equations . . . . . 55 2.3.2.2 The geometry of the mesh . . . . . . . . . . . . . 55 2.3.2.3 The First-order Scheme . . . . . . . . . . . . . . 56 2.3.2.4 The Second-order Scheme . . . . . . . . . . . . . 59 2.3.2.5 Implementation on the Cell Architecture . . . . . 60 2.3.2.6 Implementation on Falcon CNN-UM Architecture 62 2.3.2.7 Results and performance . . . . . . . . . . . . . . 63 2.3.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3 Investigating the Precision of PDE Solver Architectures on FP- GAs 69 3.1 The Advection Equation . . . . . . . . . . . . . . . . . . . . . . . 70 3.2 Numerical Solutions of the PDEs . . . . . . . . . . . . . . . . . . 70 3.2.1 The First-order Discretization . . . . . . . . . . . . . . . . 71 3.2.2 The Second-order Limited Scheme . . . . . . . . . . . . . . 72 3.3 Testing Methodology . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.4 Properties of the Arithmetic Units on FPGA . . . . . . . . . . . . 74 3.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4 Implementing a Global Analogic Programming Unit for Emulated Digital CNN Processors on FPGA 87 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4.2 Computational background and the optimized Falcon architecture 89 4.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.3.1 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.3.2 Implementation of GAPU . . . . . . . . . . . . . . . . . . 94
CONTENTS iii 4.3.3 Operating Steps . . . . . . . . . . . . . . . . . . . . . . . . 97 4.4 The real image processing system . . . . . . . . . . . . . . . . . . 98 4.5 An Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.6 Device utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 4.7 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 4.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 5 Summary of new scientific results 109 5.1 Új tudományos eredmények (magyar nyelven) . . . . . . . . . . . 113 5.2 Application of the results . . . . . . . . . . . . . . . . . . . . . . . 118 5.2.1 Application of the Fluid Flow Simulation . . . . . . . . . . 118 5.2.2 Examining the accuracy of the results . . . . . . . . . . . . 118 5.2.3 The importance of Global Analogic Programming Unit . . 119 References 128
Page 1: An Optimal Mapping of Numerical Sim
Page 5 and 6: Acknowledgements It is not so hard
Page 7: Contents 1 Introduction 1 1.1 Cellu
Page 12 and 13: vi LIST OF FIGURES 2.4 Performance
Page 15: List of Tables 2.1 Comparison of di
Page 18 and 19: xii LIST OF ABBREVIATIONS FPE Falco
Page 21 and 22: Chapter 1 Introduction Due to the r
Page 23 and 24: 3 can be represented in arbitrary t
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Page 27 and 28: 1.2 Cellular Neural/Nonlinear Netwo
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Page 33 and 34: 1.4 Field Programmable Gate Arrays
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2.1 Introduction 39 Instruction his
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2.1 Introduction 41 2E+07 1E+07 9E+
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2.1 Introduction 43 Main memory 8 t
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2.1 Introduction 45 6 4.5 3 Speedup
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2.1 Introduction 47 2.50E+07 1.88E+
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2.2 Ocean model and its implementat
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3.6 Conclusion 85 point and the 40
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4. IMPLEMENTING A GLOBAL ANALOGIC P
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References The author’s journal p
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5.2 Application of the results 123
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