Introduction to Parallel Processing Algorithms and Architectures 1st Edition by Behrooz Parhami ISBN 9780306469640 0306469642

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ISBN 10: 0306469642
ISBN 13: 9780306469640
Author: Behrooz Parhami

Introduction to Parallel Processing Algorithms and Architectures 1st Edition Table of contents:

Part I: Foundations of Parallel Processing

2. Fundamentals of Parallel Computing

   • Basic Concepts in Parallelism
   • Shared Memory vs. Distributed Memory Architectures
   • Speedup, Efficiency, and Scalability
   • Performance Metrics and Benchmarking
   • Amdahl’s Law and Gustafson’s Law

3. Parallel Programming Models

   • Parallel Algorithms and Their Classes
   • Task Parallelism and Data Parallelism
   • Synchronization and Coordination in Parallel Systems
   • Programming Models: Shared Memory, Message Passing, and Dataflow
   • Parallel Programming Languages and Tools (MPI, OpenMP, CUDA)

4. Architectures for Parallel Processing

   • Overview of Parallel Architectures
   • Flynn’s Taxonomy: SISD, SIMD, MIMD, and MISD
   • Multicore Processors and Multiprocessor Systems
   • Distributed Systems and Clusters
   • The Role of GPUs in Parallel Computing

Part II: Parallel Algorithms

5. Parallel Algorithms: Basic Principles

   • Divide and Conquer Algorithms in Parallel
   • Recursion and Parallelism
   • Task Scheduling and Load Balancing
   • Data Decomposition Strategies
   • Communication Patterns and Bottlenecks

6. Sorting and Searching Algorithms

   • Parallel Sorting Algorithms: Merge Sort, Quick Sort
   • Parallel Searching Algorithms: Binary Search, Hashing
   • Sorting Networks and Bitonic Sort
   • Performance Analysis of Parallel Sorting and Searching

7. Matrix Operations and Linear Algebra

   • Matrix Multiplication and Its Parallelization
   • Solving Linear Systems in Parallel
   • Eigenvalue and Singular Value Decomposition Algorithms
   • Applications in Scientific Computing and Engineering

8. Graph Algorithms and Parallelism

   • Parallel Depth-First and Breadth-First Search
   • Shortest Path Algorithms: Dijkstra’s and Bellman-Ford
   • Minimum Spanning Tree Algorithms
   • Parallel Algorithms for Network Flow Problems
   • Applications in Social Networks and Computational Biology

Part III: Advanced Topics in Parallel Processing

9. Parallel Computational Models

   • PRAM (Parallel Random Access Machine) Model
   • BSP (Bulk Synchronous Parallel) Model
   • LogP Model and Its Applications
   • Theoretical Foundations and Lower Bounds in Parallel Algorithms
   • The Impact of Architectural Constraints on Parallel Algorithms

10. Fault Tolerance and Reliability in Parallel Systems

    • Fault Tolerance Techniques: Redundancy and Recovery
    • Checkpointing and Rollback Mechanisms
    • Reliability in Distributed and Parallel Systems
    • Handling Failures in High-Performance Computing Systems

11. Parallelism in Machine Learning and Artificial Intelligence

    • Parallel Algorithms for Training Machine Learning Models
    • Distributed Deep Learning and GPU Acceleration
    • Parallelism in Search Algorithms and Heuristics
    • Applications in Natural Language Processing and Computer Vision

Part IV: Applications of Parallel Processing

12. High-Performance Computing Applications

    • Parallelism in Scientific Simulations and Modeling
    • Parallel Algorithms in Physics, Chemistry, and Engineering
    • Weather Forecasting, Fluid Dynamics, and Molecular Simulations
    • Supercomputing and National Laboratories

13. Parallelism in Real-Time Systems

    • Real-Time Scheduling and Task Allocation
    • Parallel Algorithms for Real-Time Data Processing
    • Applications in Embedded Systems, Robotics, and Control Systems
    • Meeting Timing Constraints in Parallel Systems

14. Cloud Computing and Big Data

    • Parallelism in Cloud Computing Architectures
    • Distributed Storage and Data Processing in the Cloud
    • Big Data Analytics and Parallel Processing
    • MapReduce and Spark for Large-Scale Data Processing

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