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Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim
| Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim |
| Autore | Suh Jung W |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Waltham, MA : , : Morgan Kaufmann, , 2014 |
| Descrizione fisica | 1 online resource (259 p.) |
| Disciplina | 518.0285 |
| Altri autori (Persone) | KimYoungmin |
| Soggetto topico | Graphics processing units - Programming |
| Soggetto genere / forma | Electronic books. |
| 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. | UNISA-996426331403316 |
Suh Jung W
|
||
| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim
| Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim |
| Autore | Suh Jung W |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Waltham, MA : , : Morgan Kaufmann, , 2014 |
| Descrizione fisica | 1 online resource (259 p.) |
| Disciplina | 518.0285 |
| Altri autori (Persone) | KimYoungmin |
| Soggetto topico | Graphics processing units - Programming |
| Soggetto genere / forma | Electronic books. |
| 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-9910453700903321 |
|
Suh Jung W
|
||
| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim
| Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim |
| 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 |
|
Suh Jung W
|
||
| Waltham, MA : , : Morgan Kaufmann, an imprint of Elsevier, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim
| Accelerating MATLAB with GPU computing : a primer with examples / / Jung W. Suh, Youngmin Kim |
| 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-9910814428703321 |
|
Suh Jung W
|
||
| Waltham, MA : , : Morgan Kaufmann, an imprint of Elsevier, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||