Masters of Computer Applications:Parallel and Distributed Computing

Thapar University
In Patiala

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Important information

  • Master
  • Patiala
  • Duration:
    3 Years
Description

Important information
Venues

Where and when

Starts Location
On request
Patiala
Thapar University P.O Box 32, 147004, Punjab, India
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Frequent Asked Questions

· Requirements

Recognised Bachelors degree of minimum 3 years duration in any discipline with Mathematics at least at 10+2 school level and has also qualified in the Entrance Test to be conducted by the University.OR Recognised Bachelor's Degree of minimum 3 years duration in any discipline with Mathematics as one of the subjects and has also qualified in the Entrance Test to be conducted by the University.

Course programme

Semester I

Discrete Mathematical Structures
Elements of Electronics Engineering
Problem Solving and Programming in C
Operating Systems
Computer Organization and Architecture


Semester II

Data Structures
Fundamental of Microprocessors and Interfacing
Object Oriented Programming using c++ and Java
System Analysis and Design
Statistics and Combinatorics


Semester III

Software Engineering
Data Base Management System
Design and Analysis of Algorithms
Operations Research
Computer Networks


Semester IV

Advanced Java and Network Programming
Computer Graphics and Multimedia
ERP and Tools
Minor Project


Semester V

Information and Network Security
Software Project Management
Net Framework and C# Programming


Semester VI

System Development Project


Parallel and Distributed Computing

Introduction: Parallel Computing Basic concepts and key issues, Classification, Serial versus parallel processing, Parallel processing applications.

Program and Network Properties: Conditions of Parallelism, Hardware versus Software Parallelism, Program partitioning and scheduling- Grain size/granularity, Latency, Levels of parallelism, Grain packing and scheduling, Program flow mechanisms- Control follow, Data flow, Demand-driven, System Interconnect Architectures- Network characteristics, Static networks and dynamic networks. Performance metrics and measures.

Architecture: Single Instruction Multiple Data (SIMD) and Multiple Instruction Multiple Data (MIMD) architectures, Shared memory multiprocessors: uniform memory access (UMA), non-uniform memory access (NUMA) and cache only memory access (COMA) model, Distributed memory multicomputers. Synchronization, Cache coherence problem. Distributed computing issues, message passing model, Remote Procedure Calls. Parallel languages

Algorithms: Parallel algorithms- Broadcast & reduction- Task partitioning & load balancing.

Laboratory Work: Simulation of SIMD/MIMD architectures using PVM/MPI.


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