Parallel and Distributed Computing

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KHUDKIBOOK
PARALLEL AND DISTRIBUTED 3170721
FREE PDF 3170721
Code: 3170721 Credits: 4 Semester 7 CSE

Parallel and Distributed Computing

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Parallel and Distributed Computing Syllabus — Unit-wise Content

The official GTU curriculum for Parallel and Distributed Computing (subject code 3170721) as prescribed for CSE · Semester 7 divides the course into 4 units, covering 41 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (3170721)

Unit 1 Introduction to Parallel Computing

5 lecture hours

  • The Idea of Parallelism
  • Power and potential of parallelism
  • Examining sequential and parallel programs
  • Scope and issues of parallel and distributed computing
  • Goals of parallelism
  • Parallelism and concurrency using multiple instructions streams

Unit 2 Parallel Architecture

10 lecture hours

  • Pipeline architecture
  • Array processor
  • Multi processor architecture
  • Systolic architecture
  • Dataflow architecture
  • Architectural classification schemes
  • Memory access classification
  • Memory Issues : Shared vs. distributed
  • Symmetric multiprocessing (SMP)
  • Vector processing
  • GPU co-processing
  • Flynn’s Taxonomy
  • Instruction Level support for parallel programming
  • Multiprocessor caches and Cache Coherence
  • Non-Uniform Memory Access (NUMA)

Unit 3 Parallel Algorithm Design Principles and Programming

10 lecture hours

  • Need for communication and coordination/synchronization
  • Scheduling and contention
  • Independence and partitioning
  • Task- Based Decomposition
  • Data Parallel Decomposition
  • Characteristics of task and interaction
  • Load balancing
  • Data Management
  • parallel algorithm models
  • Sources of overhead in parallel programs
  • Performance metrics for parallel algorithm implementations
  • Parallel algorithmic patterns like divide and conquer
  • Map and Reduce
  • Specific algorithms like parallel Merge Sort
  • Parallel graph Algorithms

Unit 4 Introduction to Distributed Systems

  • Goals of the Distributed Systems
  • Relation to parallel systems
  • synchronous versus asynchronous execution
  • design issues and challenges
  • Types of Distributed 06 Subject Code: 3170721 w.e.f

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