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3D modeling & surfacing / Bill Fleming
| 3D modeling & surfacing / Bill Fleming |
| Autore | FLEMING, Bill |
| Pubbl/distr/stampa | San Diego [etc.] : Morgan Kaufmann, copyr. 1999 |
| Descrizione fisica | XII, 340 p. : ill. ; 24 cm. + + CD ROM |
| Disciplina | 006.6 |
| Soggetto non controllato | Grafica - Programmi per microelaboratori |
| ISBN | 0-12-260490-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-990000063190203316 |
FLEMING, Bill
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| San Diego [etc.] : Morgan Kaufmann, copyr. 1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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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 |
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Suh Jung W
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| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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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 |
| Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2014 |
| Descrizione fisica | Testo elettronico (PDF) (X, 248 p. : ill.) |
| Disciplina | 519.4028553 |
| Altri autori (Persone) | KIM, Youngmin |
| Soggetto topico |
Matlab |
| ISBN | 978-0-12-408080-5 |
| Formato | Risorse elettroniche  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996444844803316 |
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SUH, Jung W
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| Waltham, MA, : Morgan Kaufmann, 2014 | ||
| Risorse elettroniche | ||
| Lo trovi qui: Univ. di Salerno | ||
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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. | UNINA-9910453700903321 |
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Suh Jung W
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| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes
| Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
| Autore | Hughes Ralph <1959-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
| Descrizione fisica | 1 online resource (379 p.) |
| Disciplina | 005.74/5 |
| Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
| ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
| Record Nr. | UNINA-9910785504103321 |
|
Hughes Ralph <1959->
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| Waltham, MA, : Morgan Kaufmann, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes
| Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
| Autore | Hughes Ralph <1959-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
| Descrizione fisica | 1 online resource (379 p.) |
| Disciplina | 005.74/5 |
| Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
| ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
| Record Nr. | UNINA-9910825750903321 |
|
Hughes Ralph <1959->
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| Waltham, MA, : Morgan Kaufmann, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik
| Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Amsterdam : , : Morgan Kaufmann, , [2014] |
| Descrizione fisica | 1 online resource (433 p.) |
| Disciplina | 005.1/2 |
| Altri autori (Persone) |
Ali BabarMuhammad
MistríkIvan |
| Soggetto topico |
Agile software development
Software architecture |
| Soggetto genere / forma | Electronic books. |
| ISBN | 0-12-407885-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Chapter 1: Introduction to ASA ASA: The State-of-the-Art ASA: Industrial/commercial perspective ASA: Current Challenges and Future Directions Part I: Fundamentals of Agile Architecting Chapter 2: The DCI Paradigm: Beyond Class-Oriented Architecture to Object Orientation Chapter 3: Refactoring software architecture Chapter 4: Architecture Decisions: Who, How and When? Part II: Managing Software Architecture in Agile Projects Chapter 5: Combining agile development and variability handling to achieve adaptable software architectures Chapter 6: Agile software architecture knowledge management Chapter 7: Continuous software architecture analysis Chapter 8: Bridging user stories and software architectures: a guidance support for agile architecting Part III: Agile Architecting in Specific Domains Chapter 9: Architecture-centric testing for security: An agile perspective Chapter 10: Multi-tenancy multi-target architectures: Extending multi-tenancy architectures for agile deployment and development Part IV: Industrial Viewpoints on Agile Architecting Chapter 11: Bursting the Agile Bubble Anti-Pattern Chapter 12: Building a Platform for Innovation: Architecture and Agile as Key Enablers Chapter 13: Opportunities, threats and limitations of emergent architecture Chapter 14: Aviva GI: Architecture as a Key Driver for Agile Success. |
| Record Nr. | UNINA-9910453480703321 |
| Amsterdam : , : Morgan Kaufmann, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik
| Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Waltham, MA : , : Morgan Kaufmann, , 2014 |
| Descrizione fisica | 1 online resource (xl, 392 pages) : illustrations (some color) |
| Disciplina | 005.1/2 |
| Collana | Gale eBooks |
| Soggetto topico |
Agile software development
Software architecture |
| ISBN | 0-12-407885-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Chapter 1: Introduction to ASA ASA: The State-of-the-Art ASA: Industrial/commercial perspective ASA: Current Challenges and Future Directions Part I: Fundamentals of Agile Architecting Chapter 2: The DCI Paradigm: Beyond Class-Oriented Architecture to Object Orientation Chapter 3: Refactoring software architecture Chapter 4: Architecture Decisions: Who, How and When? Part II: Managing Software Architecture in Agile Projects Chapter 5: Combining agile development and variability handling to achieve adaptable software architectures Chapter 6: Agile software architecture knowledge management Chapter 7: Continuous software architecture analysis Chapter 8: Bridging user stories and software architectures: a guidance support for agile architecting Part III: Agile Architecting in Specific Domains Chapter 9: Architecture-centric testing for security: An agile perspective Chapter 10: Multi-tenancy multi-target architectures: Extending multi-tenancy architectures for agile deployment and development Part IV: Industrial Viewpoints on Agile Architecting Chapter 11: Bursting the Agile Bubble Anti-Pattern Chapter 12: Building a Platform for Innovation: Architecture and Agile as Key Enablers Chapter 13: Opportunities, threats and limitations of emergent architecture Chapter 14: Aviva GI: Architecture as a Key Driver for Agile Success. |
| Record Nr. | UNINA-9910790747603321 |
| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik
| Agile software architecture : aligning agile processes and software architectures / / edited by Muhammad Ali Babar, Alan W. Brown, Ivan Mistrik |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Waltham, MA : , : Morgan Kaufmann, , 2014 |
| Descrizione fisica | 1 online resource (xl, 392 pages) : illustrations (some color) |
| Disciplina | 005.1/2 |
| Collana | Gale eBooks |
| Soggetto topico |
Agile software development
Software architecture |
| ISBN | 0-12-407885-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Chapter 1: Introduction to ASA ASA: The State-of-the-Art ASA: Industrial/commercial perspective ASA: Current Challenges and Future Directions Part I: Fundamentals of Agile Architecting Chapter 2: The DCI Paradigm: Beyond Class-Oriented Architecture to Object Orientation Chapter 3: Refactoring software architecture Chapter 4: Architecture Decisions: Who, How and When? Part II: Managing Software Architecture in Agile Projects Chapter 5: Combining agile development and variability handling to achieve adaptable software architectures Chapter 6: Agile software architecture knowledge management Chapter 7: Continuous software architecture analysis Chapter 8: Bridging user stories and software architectures: a guidance support for agile architecting Part III: Agile Architecting in Specific Domains Chapter 9: Architecture-centric testing for security: An agile perspective Chapter 10: Multi-tenancy multi-target architectures: Extending multi-tenancy architectures for agile deployment and development Part IV: Industrial Viewpoints on Agile Architecting Chapter 11: Bursting the Agile Bubble Anti-Pattern Chapter 12: Building a Platform for Innovation: Architecture and Agile as Key Enablers Chapter 13: Opportunities, threats and limitations of emergent architecture Chapter 14: Aviva GI: Architecture as a Key Driver for Agile Success. |
| Record Nr. | UNINA-9910823616903321 |
| Waltham, MA : , : Morgan Kaufmann, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
An introduction to parallel programming / Peter S. Pacheco, Malensek Matthew
| An introduction to parallel programming / Peter S. Pacheco, Malensek Matthew |
| Autore | PACHECO, Peter S. |
| Edizione | [2.ed.] |
| Pubbl/distr/stampa | Cambridge, : Morgan Kaufmann, 2022 |
| Descrizione fisica | XIX, 468 p. : ill. ; 24 cm |
| Disciplina | 005.2752 |
| Altri autori (Persone) | MALENSEK, Matthew |
| Soggetto topico |
Dati - Elaborazione parallela
Programmazione parallela |
| ISBN | 978-0-12-804605-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | und |
| Record Nr. | UNISA-996437851203316 |
|
PACHECO, Peter S.
|
||
| Cambridge, : Morgan Kaufmann, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
