Overview of Programming Models Used 1. When to Use Which Model? Organization of this Book 1. Summary ch. Vocabulary and Notation 2. Strategies 2. Mechanisms 2. Machine Models 2. Machine Model 2. Key Features for Performance 2. Flynn's Characterization 2. Evolution 2. Performance Theory 2. Latency and Throughput 2.

Speedup, Efficiency, and Scalability 2. Power 2. Amdahl's Law 2. Gustafson-Barsis' Law 2. Work-Span Model 2. Asymptotic Complexity 2. Asymptotic Speedup and Efficiency 2. Little's Formula 2. Pitfalls 2. Race Conditions 2. Mutual Exclusion and Locks 2. Deadlock 2. Strangled Scaling 2. Lack of Locality 2. Load Imbalance 2. Overhead 2. Summary pt. Nesting Pattern 3. Structured Serial Control Flow Patterns 3. Sequence 3. Selection 3. Iteration 3. Recursion 3.

- Cerebral Control of Speech and Limb Movements.
- Account Options;
- Strategic Perspectives on Social Policy.
- Structured Parallel Programming Patterns For Efficient Computation;
- Structured Parallel Programming: Patterns for Efficient Computation;
- Game Theoretical Foundations of Evolutionary Stability.
- Interactive Videoconferencing and Collaborative Distance Learning for K-12 Students and Teachers: Theory and Practice.

Parallel Control Patterns 3. Fork-Join 3. Map 3. Stencil 3. Reduction 3. Scan 3. Recurrence 3. Serial Data Management Patterns 3. Random Read and Write 3. Stack Allocation 3. Heap Allocation 3. Closures 3. Objects 3.

## Structured Parallel Programming: Patterns for Efficient Computation

Parallel Data Management Patterns 3. Pack 3. Pipeline 3. Geometric Decomposition 3. Gather 3. Scatter 3. Other Parallel Patterns 3. Superscalar Sequences 3. Futures 3. Speculative Selection 3.

## Structured Parallel Programming | Structured Parallel Programming

Workpile 3. Search 3. Segmentation 3. Expand 3. Category Reduction 3. Term Graph Rewriting 3. Non-Deterministic Patterns 3. Branch and Bound 3.

Transactions 3. Programming Model Support for Patterns 3. Cilk Plus 3. Threading Building Blocks 3. OpenMP 3. Array Building Blocks 3. OpenCL 3. Map 4. Description of the Problem 4. Serial Implementation 4. TBB 4. Cilk Plus 4. Mastering Algorithms with Perl. Jarkko Hietaniemi. Essential Algorithms. Rod Stephens. Heterogeneous Computing with OpenCL. Benedict Gaster. Assembly Language Programming. Vincent Mahout. Andrew Rushton. Learning OpenCV 3. Adrian Kaehler. Rob Farber. Ronald Sass. Maurice Herlihy. Algorithms in C, Parts Introduction to Computer Science.

Mark McIlroy. The Design and Implementation of the 4. Marshall Kirk McKusick.

Algorithms in a Nutshell. George T. Computer Science. CUDA Programming. Shane Cook. Schaum's Outline of Data Structures with Java, 2ed. John R. Algorithms and Parallel Computing. Fayez Gebali. Control Software for Mechanical Systems. Algorithms, Part II. Nicholas Wilt. Kubernetes: Up and Running. Kelsey Hightower. VMware Cookbook. Ryan Troy. Cloud Application Architectures. George Reese.

Modern Compiler Implementation in C. Andrew W. Programming Google App Engine. Dan Sanderson. Raymond Tay. Ryan Cartwright. Infrastructure as Code. Kief Morris. Getting Started with Citrix XenApp 6. Guillermo Musumeci. Peter J. Data Structures I Essentials. Dennis Smolarski. OpenStack Operations Guide. Newsletter Receba descontos especiais e ofertas exclusivas no seu email. Newsletter Nome:.

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