Autore	Suh Jung W
Edizione	[First edition.]
Pubbl/distr/stampa	Waltham, MA : , : Morgan Kaufmann, an imprint of Elsevier, , 2014
Descrizione fisica	1 online resource (x, 248 pages) : illustrations (some color)
Disciplina	518.0285
Collana	Gale eBooks
Soggetto topico	Graphics processing units Numerical analysis - Data processing
ISBN	0-12-407916-4
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Front Cover; Accelerating MATLAB with GPU Computing; Copyright Page; Contents; Preface; Target Readers and Contents; Directions of this Book; GPU Utilization Using c-mex Versus Parallel Computing Toolbox; Tutorial Approach Versus Case Study Approach; CUDA Versus OpenCL; 1 Accelerating MATLAB without GPU; 1.1 Chapter Objectives; 1.2 Vectorization; 1.2.1 Elementwise Operation; 1.2.2 Vector/Matrix Operation; 1.2.3 Useful Tricks; 1.3 Preallocation; 1.4 For-Loop; 1.5 Consider a Sparse Matrix Form; 1.6 Miscellaneous Tips; 1.6.1 Minimize File Read/Write Within the Loop 1.6.2 Minimize Dynamically Changing the Path and Changing the Variable Class 1.6.3 Maintain a Balance Between the Code Readability and Optimization; 1.7 Examples; 2 Configurations for MATLAB and CUDA; 2.1 Chapter Objectives; 2.2 MATLAB Configuration for c-mex Programming; 2.2.1 Checklists; 2.2.1.1 C/C++ Compilers; 2.2.1.2 NVIDIA CUDA Compiler nvcc; 2.2.2 Compiler Selection; 2.3 "Hello, mex!" using C-MEX; 2.3.1.1 Summary; 2.4 CUDA Configuration for MATLAB; 2.4.1 Preparing CUDA Settings; 2.5 Example: Simple Vector Addition Using CUDA; 2.5.1.1 Summary; 2.6 Example with Image Convolution 2.6.1 Convolution in MATLAB 2.6.2 Convolution in Custom c-mex; 2.6.3 Convolution in Custom c-mex with CUDA; 2.6.4 Brief Time Performance Profiling; 2.7 Summary; 3 Optimization Planning through Profiling; 3.1 Chapter Objectives; 3.2 MATLAB Code Profiling to Find Bottlenecks; 3.2.1 More Accurate Profiling with Multiple CPU Cores; 3.3 c-mex Code Profiling for CUDA; 3.3.1 CUDA Profiling Using Visual Studio; 3.3.2 CUDA Profiling Using NVIDIA Visual Profiler; 3.4 Environment Setting for the c-mex Debugger; 4 CUDA Coding with c-mex; 4.1 Chapter Objectives; 4.2 Memory Layout for c-mex 4.2.1 Column-Major Order 4.2.2 Row-Major Order; 4.2.3 Memory Layout for Complex Numbers in c-mex; 4.3 Logical Programming Model; 4.3.1 Logical Grouping 1; 4.3.2 Logical Grouping 2; 4.3.3 Logical Grouping 3; 4.4 Tidbits of GPU; 4.4.1 Data Parallelism; 4.4.2 Streaming Processor; 4.4.3 Steaming Multiprocessor; 4.4.4 Warp; 4.4.5 Memory; 4.5 Analyzing Our First Naïve Approach; 4.5.1 Optimization A: Thread Blocks; 4.5.2 Optimization B; 4.5.3 Conclusion; 5 MATLAB and Parallel Computing Toolbox; 5.1 Chapter Objectives; 5.2 GPU Processing for Built-in MATLAB Functions; 5.2.1 Pitfalls in GPU Processing 5.3 GPU Processing for Non-Built-in MATLAB Functions 5.4 Parallel Task Processing; 5.4.1 MATLAB Worker; 5.4.2 parfor; 5.5 Parallel Data Processing; 5.5.1 spmd; 5.5.2 Distributed and Codistributed Arrays; 5.5.3 Workers with Multiple GPUs; 5.6 Direct use of CUDA Files without c-mex; 6 Using CUDA-Accelerated Libraries; 6.1 Chapter Objectives; 6.2 CUBLAS; 6.2.1 CUBLAS Functions; 6.2.2 CUBLAS Matrix-by-Matrix Multiplication; 6.2.2.1 Step 1; 6.2.2.2 Step 2; 6.2.2.3 Step 3; 6.2.2.4 Step 4; 6.2.2.5 Step 5; 6.2.2.6 Step 6; 6.2.2.7 Step 7; 6.2.2.8 Step 8; 6.2.2.9 Step 9 6.2.3 CUBLAS with Visual Profiler
Record Nr.	UNINA-9910790838903321

Pubbl/distr/stampa	[New York], : ACM Press, -1998
Disciplina	519.4
Soggetto topico	Numerical analysis - Data processing
Soggetto genere / forma	Periodicals.
ISSN	1558-0237
Formato	Materiale a stampa
Livello bibliografico	Periodico
Lingua di pubblicazione	eng
Altri titoli varianti	Signum newsletter
Record Nr.	UNISA-996200952903316

Autore	Radi Bouchaïb
Pubbl/distr/stampa	London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2018
Descrizione fisica	1 online resource (36 pages) : illustrations, tables
Disciplina	518.028553
Collana	Mathematical and Mechanical Engineering Set
Soggetto topico	Numerical analysis - Data processing Engineering mathematics
ISBN	1-119-51655-2 1-119-51654-4 1-119-45361-5
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910271020103321

Pubbl/distr/stampa	Budapest, : Eötvös Loránd Tudományegyetem, 1978-
Descrizione fisica	1 online resource
Disciplina	519.4/05
Soggetto topico	Numerical analysis Numerical analysis - Data processing Mathematical analysis Mathematical analysis - Data processing Wiskunde Toepassingen Mathematik Zeitschrift
Soggetto genere / forma	Periodicals.
Formato	Materiale a stampa
Livello bibliografico	Periodico
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910144071503321

Autore	Yang Won Y
Edizione	[2nd ed.]
Pubbl/distr/stampa	Newark : , : John Wiley & Sons, Incorporated, , 2020
Descrizione fisica	1 online resource (653 pages)
Disciplina	518
Altri autori (Persone)	CaoWenwu KimJaekwon ParkKyung W ParkHo-Hyun JoungJingon RoJong-Suk LeeHan L HongCheol-Ho ImTaeho
Soggetto topico	Numerical analysis - Data processing
ISBN	1-5231-5509-4 1-119-62682-X 1-119-62687-0 1-119-62671-4
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- About the Companion Website -- Chapter 1 MATLAB Usage and Computational Errors -- 1.1 Basic Operations of MATLAB -- 1.1.1 Input/Output of Data from MATLAB Command Window -- 1.1.2 Input/Output of Data Through Files -- 1.1.3 Input/Output of Data Using Keyboard -- 1.1.4 Two‐Dimensional (2D) Graphic Input/Output -- 1.1.5 Three Dimensional (3D) Graphic Output -- 1.1.6 Mathematical Functions -- 1.1.7 Operations on Vectors and Matrices -- 1.1.8 Random Number Generators -- 1.1.9 Flow Control -- 1.2 Computer Errors vs. Human Mistakes -- 1.2.1 IEEE 64‐bit Floating‐Point Number Representation -- 1.2.2 Various Kinds of Computing Errors -- 1.2.3 Absolute/Relative Computing Errors -- 1.2.4 Error Propagation -- 1.2.5 Tips for Avoiding Large Errors -- 1.3 Toward Good Program -- 1.3.1 Nested Computing for Computational Efficiency -- 1.3.2 Vector Operation vs. Loop Iteration -- 1.3.3 Iterative Routine vs. Recursive Routine -- 1.3.4 To Avoid Runtime Error -- 1.3.5 Parameter Sharing via GLOBAL Variables -- 1.3.6 Parameter Passing Through VARARGIN -- 1.3.7 Adaptive Input Argument List -- Chapter 2 System of Linear Equations -- 2.1 Solution for a System of Linear Equations -- 2.1.1 The Nonsingular Case (M & -- equals -- N) -- 2.1.2 The Underdetermined Case (M < -- N): Minimum‐norm Solution -- 2.1.3 The Overdetermined Case (M > -- N): Least‐squares Error Solution -- 2.1.4 Recursive Least‐Squares Estimation (RLSE) -- 2.2 Solving a System of Linear Equations -- 2.2.1 Gauss(ian) Elimination -- 2.2.2 Partial Pivoting -- 2.2.3 Gauss‐Jordan Elimination -- 2.3 Inverse Matrix -- 2.4 Decomposition (Factorization) -- 2.4.1 LU Decomposition (Factorization) - Triangularization -- 2.4.2 Other Decomposition (Factorization) - Cholesky, QR and SVD -- 2.5 Iterative Methods to Solve Equations. 2.5.1 Jacobi Iteration -- 2.5.2 Gauss‐Seidel Iteration -- 2.5.3 The Convergence of Jacobi and Gauss‐Seidel Iterations -- Chapter 3 Interpolation and Curve Fitting -- 3.1 Interpolation by Lagrange Polynomial -- 3.2 Interpolation by Newton Polynomial -- 3.3 Approximation by Chebyshev Polynomial -- 3.4 Pade Approximation by Rational Function -- 3.5 Interpolation by Cubic Spline -- 3.6 Hermite Interpolating Polynomial -- 3.7 Two‐Dimensional Interpolation -- 3.8 Curve Fitting -- 3.8.1 Straight‐Line Fit - A Polynomial Function of Degree 1 -- 3.8.2 Polynomial Curve Fit - A Polynomial Function of Higher Degree -- 3.8.3 Exponential Curve Fit and Other Functions -- 3.9 Fourier Transform -- 3.9.1 FFT vs. DFT -- 3.9.2 Physical Meaning of DFT -- 3.9.3 Interpolation by Using DFS -- Chapter 4 Nonlinear Equations -- 4.1 Iterative Method toward Fixed Point -- 4.2 Bisection Method -- 4.3 False Position or Regula Falsi Method -- 4.4 Newton(‐Raphson) Method -- 4.5 Secant Method -- 4.6 Newton Method for a System of Nonlinear Equations -- 4.7 Bairstow's Method for a Polynomial Equation -- 4.8 Symbolic Solution for Equations -- 4.9 Real‐World Problems -- Chapter 5 Numerical Differentiation/Integration -- 5.1 Difference Approximation for the First Derivative -- 5.2 Approximation Error of the First Derivative -- 5.3 Difference Approximation for Second and Higher Derivative -- 5.4 Interpolating Polynomial and Numerical Differential -- 5.5 Numerical Integration and Quadrature -- 5.6 Trapezoidal Method and Simpson Method -- 5.7 Recursive Rule and Romberg Integration -- 5.8 Adaptive Quadrature -- 5.9 Gauss Quadrature -- 5.9.1 Gauss‐Legendre Integration -- 5.9.2 Gauss‐Hermite Integration -- 5.9.3 Gauss‐Laguerre Integration -- 5.9.4 Gauss‐Chebyshev Integration -- 5.10 Double Integral -- 5.11 Integration Involving PWL Function -- Chapter 6 Ordinary Differential Equations. 6.1 Euler's Method -- 6.2 Heun's Method - Trapezoidal Method -- 6.3 Runge‐Kutta Method -- 6.4 Predictor‐Corrector Method -- 6.4.1 Adams‐Bashforth‐Moulton Method -- 6.4.2 Hamming Method -- 6.4.3 Comparison of Methods -- 6.5 Vector Differential Equations -- 6.5.1 State Equation -- 6.5.2 Discretization of LTI State Equation -- 6.5.3 High‐order Differential Equation to State Equation -- 6.5.4 Stiff Equation -- 6.6 Boundary Value Problem (BVP) -- 6.6.1 Shooting Method -- 6.6.2 Finite Difference Method -- Chapter 7 Optimization -- 7.1 Unconstrained Optimization -- 7.1.1 Golden Search Method -- 7.1.2 Quadratic Approximation Method -- 7.1.3 Nelder‐Mead Method -- 7.1.4 Steepest Descent Method -- 7.1.5 Newton Method -- 7.1.6 Conjugate Gradient Method -- 7.1.7 Simulated Annealing -- 7.1.8 Genetic Algorithm -- 7.2 Constrained Optimization -- 7.2.1 Lagrange Multiplier Method -- 7.2.2 Penalty Function Method -- 7.3 MATLAB Built‐In Functions for Optimization -- 7.3.1 Unconstrained Optimization -- 7.3.2 Constrained Optimization -- 7.3.3 Linear Programming (LP) -- 7.3.4 Mixed Integer Linear Programming (MILP) -- 7.4 Neural Network[K‐1] -- 7.5 Adaptive Filter[Y‐3] -- 7.6 Recursive Least Square Estimation (RLSE)[Y‐3] -- Chapter 8 Matrices and Eigenvalues -- 8.1 Eigenvalues and Eigenvectors -- 8.2 Similarity Transformation and Diagonalization -- 8.3 Power Method -- 8.3.1 Scaled Power Method -- 8.3.2 Inverse Power Method -- 8.3.3 Shifted Inverse Power Method -- 8.4 Jacobi Method -- 8.5 Gram‐Schmidt Orthonormalization and QR Decomposition -- 8.6 Physical Meaning of Eigenvalues/Eigenvectors -- 8.7 Differential Equations with Eigenvectors -- 8.8 DoA Estimation with Eigenvectors[Y-3] -- Chapter 9 Partial Differential Equations -- 9.1 Elliptic PDE -- 9.2 Parabolic PDE -- 9.2.1 The Explicit Forward Euler Method -- 9.2.2 The Implicit Backward Euler Method. 9.2.3 The Crank‐Nicholson Method -- 9.2.4 Using the MATLAB function 'pdepe()' -- 9.2.5 Two‐Dimensional Parabolic PDEs -- 9.3 Hyperbolic PDES -- 9.3.1 The Explicit Central Difference Method -- 9.3.2 Two‐Dimensional Hyperbolic PDEs -- 9.4 Finite Element Method (FEM) for Solving PDE -- 9.5 GUI of MATLAB for Solving PDES - PDEtool -- 9.5.1 Basic PDEs Solvable by PDEtool -- 9.5.2 The Usage of PDEtool -- 9.5.3 Examples of Using PDEtool to Solve PDEs -- Appendix A Mean Value Theorem -- Appendix B Matrix Operations/Properties -- B.1 Addition and Subtraction -- B.2 Multiplication -- B.3 Determinant -- B.4 Eigenvalues and Eigenvectors of a Matrix1 -- B.5 Inverse Matrix -- B.6 Symmetric/Hermitian Matrix -- B.7 Orthogonal/Unitary Matrix -- B.8 Permutation Matrix -- B.9 Rank -- B.10 Row Space and Null Space -- B.11 Row Echelon Form -- B.12 Positive Definiteness -- B.13 Scalar (Dot) Product and Vector (Cross) Product -- B.14 Matrix Inversion Lemma -- Appendix C Differentiation W.R.T. A Vector -- Appendix D Laplace Transform -- Appendix E Fourier Transform -- Appendix F Useful Formulas -- Appendix G Symbolic Computation -- G.1 How to Declare Symbolic Variables and Handle Symbolic Expressions -- G.2 Calculus -- G.2.1 Symbolic Summation -- G.2.2 Limits -- G.2.3 Differentiation -- G.2.4 Integration -- G.2.5 Taylor Series Expansion -- G.3 Linear Algebra -- G.4 Solving Algebraic Equations -- G.5 Solving Differential Equations -- Appendix H Sparse Matrices -- Appendix I MATLAB -- References -- Index -- Index for MATLAB Functions -- Index for Tables -- EULA.
Record Nr.	UNINA-9910830712603321