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MATLAB PARALLEL COMPUTING TOOLBOX - S Handbücher

Bedienungsanleitungen und Benutzerhandbücher für Software MATLAB PARALLEL COMPUTING TOOLBOX - S.
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Matlab PARALLEL COMPUTING TOOLBOX - S Betriebsanweisung (656 Seiten)


Marke: Matlab | Kategorie: Software | Größe: 2.89 MB |

 

Inhaltsverzeichnis

Parallel Computing Toolbox™

1

User's Guide

1

How to Contact MathWorks

2

Revision History

3

Contents

5

Program Independent Jobs

11

Program Communicating Jobs

12

GPU Computing

12

Objects — Alphabetical List

14

Functions — Alphabetical List

14

Glossary

14

Getting Started

15

1 Getting Started

16

Partition Large Data Sets

19

Run a Batch Job

22

Run a Batch Parallel Loop

23

Parallel for-Loops (parfor)

29

Introduction to parfor

30

Create a parfor-Loop

32

Create a parfor-Loop

33

2 Parallel for-Loops (parfor)

34

parfor Limitations

39

Using Objects in parfor-Loops

41

Handle Classes

41

Nested Functions

43

Nested Loops

43

Nested spmd Statements

45

Break and Return Statements

45

P-Code Scripts

45

Unambiguous Variable Names

47

Transparency

47

Loop Variable

53

Sliced Variables

55

Broadcast Variables

59

Reduction Variables

60

Reduction Variables

65

Temporary Variables

67

Temporary Variables

69

Improving parfor Performance

70

Improving parfor Performance

71

Parallel Pools

72

Parallel Pools

73

Start a Parallel Pool

73

When to Use spmd

80

Define an spmd Statement

81

Display Output

83

Introduction to Composites

84

Distribute Arrays

88

Create Codistributed Arrays

89

P>> help magic

97

P>> x = pi

97

P>> x = labindex

98

P>> all = numlabs

98

P>> getLocalPart(I)

102

P>> pmode exit

103

Parallel Command Window

104

Click tiling icon

105

Select layout

105

Select vertical

106

Drag to adjust

106

Click tabbed output

107

Select only two tabs

107

Multiple labs

108

Using Graphics in pmode

112

Connectivity Testing

113

Hostname Resolution

113

Socket Connections

113

Introduction

116

Nondistributed Arrays

116

Codistributed Arrays

118

A = zeros(80, 1000);

119

D = codistributed(A)

119

Local Arrays

124

Restoring the Full Array

127

2-Dimensional Distribution

130

Parallelizing a for-Loop

134

plot(1:numDataSets, res);

135

Programming Overview

141

6 Programming Overview

142

Toolbox and Server Components

143

Life Cycle of a Job

147

Parallel Preferences

152

Parallel Preferences

153

Clusters and Cluster Profiles

154

Job Monitor

169

Job Monitor

171

Programming Tips

172

Programming Tips

173

Using the pause Function

175

Interrupting a Job

175

Speeding Up a Job

175

Control Random Number Streams

177

Client and GPU

179

Worker CPU and Worker GPU

181

Profiling Parallel Code

182

Viewing Parallel Profile Data

183

Profiling Parallel Code

185

Benchmarking Performance

191

Troubleshooting and Debugging

192

Caused by:

195

Start Parallel Pool

197

Compare Parallel mapreduce

197

See Also

199

Cluster Preparation

201

Output Format and Order

201

Calculate Mean Delay

201

Related Examples

203

More About

203

7 Program Independent Jobs

212

MJS Cluster

217

Properties

217

Share Code with the Workers

224

Share Code with the Workers

227

Overview

229

Client node

231

MATLAB client

231

Scheduler

231

MATLAB Worker Decode Function

235

Program Communicating Jobs

249

8 Program Communicating Jobs

250

Code in the Client

251

9 GPU Computing

260

Establish Arrays on a GPU

261

Establish Arrays on a GPU

265

100 100

265

Supported MATLAB Code

273

Run CUDA or PTX Code on GPU

278

Create a CUDAKernel Object

279

Run CUDA or PTX Code on GPU

281

Compile a GPU MEX-File

291

Comparison to a CUDA Kernel

291

Constructor

302

Description

302

codistributed

303

Properties

304

Composite

306

CUDAKernel

307

distributed

311

GPUDevice

314

Constructors

319

Container Hierarchy

319

parallel.Cluster

321

HPC Server

322

PBS Pro and TORQUE

322

MJS Jobs

332

CJS Jobs

332

RemoteClusterAccess

341

Examples

344

Input Arguments

346

arrayfun

349

Arguments

352

Create gpuArray False Matrix

430

Create gpuArray Inf Matrix

484

Output Arguments

513

mpiprofile

519

C Syntax

524

Create gpuArray NaN Matrix

549

Create gpuArray Rand Matrix

605

Create gpuArray True Matrix

641

Glossary

653

Glossary-5

655




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