What are the stages of parallel algorithm design?

decomposition of a computational problem into tasks that can be executed simultaneously, and development of sequential algorithms for individual tasks; analysis of computation granularity; minimizing the cost of the parallel algorithm; assigning tasks to processors executing the parallel algorithm.

What is the first step in design process of parallel algorithm?

1. Step 1: Partitioning. At the beginning of design, discover as much parallelism as possible.
2. 3 examples of domain decomposition. Parallel algorithm design – p.
3. Step 2: Communication. When primitive tasks are identified, determine the communication.
4. 2 examples of communication.
5. Step 3: Agglomeration.
6. Step 4: Mapping.

What are the important characteristics of parallel algorithm?

The data set is organized into some structure like an array, hypercube, etc. Processors perform operations collectively on the same data structure. Each task is performed on a different partition of the same data structure. It is restrictive, as not all the algorithms can be specified in terms of data parallelism.

What are the key characteristics of a parallel algorithm?

A parallel algorithm is an algorithm that can execute several instructions simultaneously on different processing devices and then combine all the individual outputs to produce the final result.

What do you mean by parallel algorithms?

In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as random-access machine.

How does the sequential algorithm work?

In computer science, a sequential algorithm or serial algorithm is an algorithm that is executed sequentially – once through, from start to finish, without other processing executing – as opposed to concurrently or in parallel.

What is parallel computing with examples?

To recap, parallel computing is breaking up a task into smaller pieces and executing those pieces at the same time, each on their own processor or computer. Some examples of parallel computing include weather forecasting, movie special effects, and desktop computer applications.

What is the purpose of parallel algorithms?