Question

Distinguish among Computer Terminologies in each of the following groups:

25 Nov 2020
Answer :
Word Count : 1493

In the context of parallel computing, it is important to understand various computer terminologies that help differentiate between the different computing paradigms, architectures, models, and components. These terms are essential for discussing the structure, behavior, and operation of parallel systems. Below is a detailed analysis of some of the common terminologies that are used in parallel computing, distinguishing them based on the groupings provided.

1. Single-core vs Multi-core Processing:

  • Single-core Processing: Single-core processing refers to the architecture where a computer system has a single processing unit (core) to execute tasks. All operations are handled by this single core, and multitasking is achieved by time-sharing, where the operating system switches between tasks to give the illusion of parallelism. However, a single-core system can only execute one instruction per clock cycle at a time.

  • Multi-core Processing: A multi-core processor contains multiple processing units (cores) within a single physical processor chip. Each core can handle its own thread of execution, which enables true parallelism. In this setup, multiple tasks or threads can be processed simultaneously, improving the performance and efficiency of a system, especially for tasks that can be divided into smaller sub-tasks or threads.

2. Parallel Computing vs Concurrent Computing:

  • Parallel Computing: Parallel computing refers to the simultaneous execution of multiple tasks or processes across multiple processing units. These processes can be performed in parallel either on multiple cores within a single processor or across multiple processors connected in a network. The goal is to divide a large task into smaller, independent tasks that can be executed simultaneously to reduce computation time.

  • Concurrent Computing: Concurrent computing refers to the execution of multiple tasks in an overlapping time period but not necessarily simultaneously. In a concurrent system, tasks may be started, run, and completed in overlapping time intervals but not necessarily at the same time. Multitasking in operating systems is an example of concurrency, where multiple tasks appear to run at the same time, but the system switches between them rapidly, giving the illusion of parallelism.

3. Shared Memory vs Distributed Memory:

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