Why Parallel Computing?

Parallel computing refers to a simultaneous use of multiple compute resource to solve a computational problem that occur such as a broken intyo discrete parts that can be solved. it should be solved in less time with multiple compute resources with a single compute resource.

Parallel computers are virtually stand-alone computers that built by hardware perspective of multiple functional units, multiple execution units/cores and multiple hardware threads.

Parallel computing is much better suited for modeling, simulating and understanding complex, real world phenomena.

In other hand, parallel computing will :

1.      SAVE TIME AND/OR MONEY:

1. In theory, throwing more resources at a task will shorten its time to completion, with potential cost savings.
2. Parallel computers can be built from cheap, commodity components.

2.      SOLVE LARGER / MORE COMPLEX PROBLEMS:

1. Many problems are so large and/or complex that it is impractical or impossible to solve them on a single computer, especially given limited computer memory.

3.      PROVIDE CONCURRENCY:

1. A single compute resource can only do one thing at a time. Multiple compute resources can do many things simultaneously.

4.      MAKE BETTER USE OF UNDERLYING PARALLEL HARDWARE:

1. Modern computers, even laptops, are parallel in architecture with multiple processors/cores.
2. Parallel software is specifically intended for parallel hardware with multiple cores, threads, etc.
3. In most cases, serial programs run on modern computers "waste" potential computing power.

Intel Xeon processor with 6 cores and 6 L3 cache units

Application of parallel computing

1  Science and Engineering

Historically, parallel computing has been considered to be "the high end of computing", and has been used to model difficult problems in many areas of science and engineering:

Atmosphere, Earth, Environment Physics - applied, nuclear, particle, condensed matter, high pressure, fusion, photonics Bioscience, Biotechnology, Genetics Chemistry, Molecular Sciences Geology, Seismology

Mechanical Engineering - from prosthetics to spacecraft Electrical Engineering, Circuit Design, Microelectronics Computer Science, Mathematics Defense, Weapons

2  Industrial and Commercial

Today, commercial applications provide an equal or greater driving force in the development of faster computers. These applications require the processing of large amounts of data in sophisticated ways. For example:

Databases, data mining Oil exploration Web search engines, web based business services Medical imaging and diagnosis Pharmaceutical design

Financial and economic modeling Management of national and multi-national corporations Advanced graphics and virtual reality, particularly in the entertainment industry Networked video and multi-media technologies Collaborative work environments