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Parallel and Distributed Computing
Parallel computing refers to the form of computation by which many calculations can be done at the same time by operating the large problems into smaller ones and then solves it parallely. There are different forms of parallel computing such as bit-level, instruction level, data, and task parallelism. Parallelism has high-performance computing. Parallel computers are classified according to the level hardware parallelism, with multi-core and multi-processor computers having multiple processing elements within a single machine, while clusters, MPPs, and grids use multiple computers to work on the same task. Communication and synchronization between different tasks are some of the hindrance to get a good parallel program performance.
On the other hand distributed computing deals with all forms of computing, information access, and information exchange across multiple processing platforms connected by computer networks. Design of distributed computing systems is a complex task that requires a solid understanding of the design issues and an in-depth understanding of the theoretical and practical aspects of their solutions. A distributed system is a collection of independent entities that cooperate to solve a problem that cannot be solved individually.
Following are some of the important topics and subfields of parallel and distributed computing:-
- Mathematical foundations
- Artificial intelligence.
- Communication and security
- Computer graphics
- Race conditions
- Mutual exclusion
- Fine-grained and coarse-grained
- Consistency models
- Resource sharing
- Concurrency control
- Deadlock detection and avoidance
- Distributed data access and control
- Consistency control
- Parallel Programming Languages
- Environments and Tools
- Parallel Algorithms Performance Issues
- Distributed Memory Systems
- Group Communication
- Fault Tolerance.
- Scalable multiprocessor systems and clusters
- virtual machine
- service oriented architecture
- network-based computing
- grid and cloud based storage and computing
- design and implementation of parallel and distributed systems
- cloud computing, grid computing, cluster computing, supercomputing
Few Topics are:
- Scalable multiprocessor systems and clusters,
- virtual machine, service oriented architecture,
- network-based computing,
- peer-to-peer, grid
- cloud based storage.