Athnere

Parallel Computing

Parallel computing is the simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain results faster. The idea is based on the fact that the process of solving a problem usually can be divided into smaller tasks, which may be carried out simultaneously with some coordination.

parallel computing is the simultaneous use of multiple compute resources to solve a computational problem.
To be run using multiple CPUs
A problem is broken into discrete parts that can be solved concurrently
Each part is further broken down to a series of instructions
Instructions from each part execute simultaneously on different CPUs
The compute resources can include:
A single computer with multiple processors;
An arbitrary number of computers connected by a network;
A combination of both.
The computational problem usually demonstrates characteristics such as the ability to be:
Broken apart into discrete pieces of work that can be solved simultaneously;
Execute multiple program instructions at any moment in time;
Solved in less time with multiple compute resources than with a single compute resource.
Parallel computing is an evolution of serial computing that attempts to emulate what has always been the state of affairs in the natural world: many complex, interrelated events happening at the same time, yet within a sequence. Some examples:
Planetary and galactic orbits
Weather and ocean patterns
Tectonic plate drift
Rush hour traffic in LA
Automobile assembly line
Daily operations within a business
Building a shopping mall
Ordering a hamburger at the drive through.
Traditionally, parallel computing has been considered to be "the high end of computing" and has been motivated by numerical simulations of complex systems and "Grand Challenge Problems" such as:
weather and climate
chemical and nuclear reactions
biological, human genome
geological, seismic activity
mechanical devices - from prosthetics to spacecraft
electronic circuits
manufacturing processes
Today, commercial applications are providing 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. Example applications include:
parallel databases, data mining
oil exploration
web search engines, web based business services
computer-aided diagnosis in medicine
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
Ultimately, parallel computing is an attempt to maximize the infinite but seemingly scarce commodity called time.
http://www.llnl.gov/computing/tutorials/parallel_comp/#Whatis

posted by abhilasha @ 3:28 AM