Masters of Computer Applications:Parallel and Distributed Computing
Master
In Patiala
Description
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Type
Master
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Location
Patiala
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Duration
3 Years
Facilities
Location
Start date
Start date
About this course
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.
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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.
Masters of Computer Applications:Parallel and Distributed Computing