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System which consists of group of networked computer who all have same task goal is called Distributed systems. It is collection of many independent computer but it visualizes to users as a single computer. This system have collection of autonomous computers, there processors have different clocks and memory and the systems are weakly coupled. The physically separated processors are connected through more than one communication link.

Processors in the distributed systems have private memories and do not share each other's memory. For sharing information messages are passed between the processors. Example of distributed system are: Telephone networks, ATM machines, etc., Distributed systems are categorized as homogeneous and heterogeneous systems.

Parallel system is a system in which multiple processors are directly accessed to share common memory and this memory forms address space which is common. These systems are tightly coupled as there is a single system having common memory which is shared by all the processors in a system. There is a global control clock and the systems have main focus on the scientific computing. The connections between the systems are done with the help of mesh, tree, bus networks. Parallel systems can directly interface with the computers present on the network.

Distributed systems have more computing speed than the parallel systems and also have good resource sharing capability as comparison to the parallel systems. But distributed
systems are more complex than the parallel systems. Parallel systems have less overheads than the distributed systems and have more execution than distributed sytem.

Parallel system is the compilation of processing elements that communicate to solve a specific problem while distributed system is the collection of independent computers that perform like a single coherent system. Distributed system do not share processors and memory and communicate with each other via communication network. Workstations network, Mobile computing, ATM machines are the example of distributed system. Parallel system is used to reduce the runtime and to improve the fault tolerance of a computational process. Parallel system contains global clock control while distributed system doesn’t contain it. Parallel system is mainly used in scientific computing.

Parallel system has tightly coupled system shared memory while distributed system has weakly coupled system distributed memory. In parallel system, single system address space is shared by the all processors. Supercomputers are the example of parallel computing.

Main advantages of parallel systems are to save time and money and could done multiple things at the same time, provide user friendly programming and advantages of distributed systems are resource sharing, provides scalability and transparency, provides better flexibility and reliability. Parallel system comes with the various issues such as data sharing, fault reliability, process coordination. In parallel system, Processor interconnection can be measured in the order of Tbps while in the distributed system , it can be measured in the terms of Gbps.

Parallel and Distributed Systems: 

Parallel and distributed computing,spectrum from theoretical models of parallel and distributed systems to actual programming assignments.

  • Principles of distributed computer systems, techniques of distributed computer systems.
  • Implementation of distributed computer systems, analysis of distributed computer systems, parallel computer systems.

Topics for Introduction to Parallel and Distributed Systems: 

  • Parallel Models,PRAM,Scan Vector Model,Complexity measures,Designing Parallel Algorithms:,Basic PRAM techniques,Doubling technique,Summation trees ,prefix summation,Interconnection networks,Graph models of networks, Network properties,Searching ,sorting ,Sorting and Searching on PRAMs:,Merge sort,Compare exchange sort,Batchers sorting algorithms,Computing the Median,Pointer based algorithms:,List ranking.
  • Tree contraction,Connected components,Minimum spanning tree;,Geometric Algorithms,Convex hulls,Closest pair of points,Visibility,Distributed Models ,distributed computation,Termination, Failure tolerance,Network topology,Distributed Search,Distributed BFS,Random walks,Markov processes,hitting time,cover time,connectivity,Distributed networks,Broadcasting,Robust distributed networks,Hardware,Applications.
  • Programming Styles ,Processes ,Synchronization ,Programming with Shared Variables ,Locks ,Barriers ,Semaphores,Monitors ,Distributed Programming ,Message Passing ,Remote Procedure Call ,Process Interaction ,Scientific Computing,Distributed Systems.

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