Parallel and Distributed Computing 3170721 Syllabus Download With Weightage

Parallel and Distributed Computing 3170721 Syllabus Download With Weightage

Parallel and Distributed Computing 3170721 is a term that refers to Computer Department covers this subject This year, this Subject is covered in the 7th Semester.   


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Introduction to Parallel Computing:

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.


Parallel Architecture:

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), SIMD, Vector
processing, GPU co-processing, Flynn’s Taxonomy, Instruction Level support for parallel
programming, Multiprocessor caches and Cache Coherence, Non-Uniform Memory
Access (NUMA).


Parallel Algorithm Design Principles and Programming:

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


Introduction to Distributed Systems:

Goals of the Distributed Systems, Relation to parallel systems, synchronous
versus asynchronous execution, design issues and challenges, Types of Distributed Systems, Distributed System Models, Hardware and software concepts related to
distributed systems, middleware models. 


Distributed Computing and Communication design principles:

A Model of distributed executions, Models of communication networks, Global state of
distributed system, Models of process communication. Communication and Coordination:
Shared Memory, Consistency, Atomicity, Message- Passing, Consensus, Conditional
Actions, Critical Paths, Scalability, and cache coherence in multiprocessor systems,
synchronization mechanism


Parallel and Distributed Programming Frameworks

Overview of CUDA, OpenMP, POSIX Threads, Apache Hadoop (DFS), and current trends
in parallel and distributed computing.



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