Editing Grid computing (section)

==Comparison of grids and conventional supercomputers==
“Distributed” or “grid” computing in general is a special type of [[parallel computing]] that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a [[computer network|network]] (private, public or the [[Internet]]) by a conventional [[Network interface controller|network interface]] producing commodity hardware, compared to the lower efficiency of designing and constructing a small number of custom supercomputers. The primary performance disadvantage is that the various processors and local storage areas do not have high-speed connections. This arrangement is thus well-suited to applications in which multiple parallel computations can take place independently, without the need to communicate intermediate results between processors.<ref>[http://www.e-sciencecity.org/EN/gridcafe/computational-problems.html Computational problems - Gridcafe] {{Webarchive|url=https://web.archive.org/web/20120825003633/http://www.e-sciencecity.org/EN/gridcafe/computational-problems.html |date=2012-08-25 }}. E-sciencecity.org. Retrieved 2013-09-18.</ref> The high-end [[scalability]] of geographically dispersed grids is generally favorable, due to the low need for connectivity between [[Node (computer science)|nodes]] relative to the capacity of the public Internet.<ref>{{Cite web |title=What is grid computing? |url=https://www.ionos.com/digitalguide/server/know-how/grid-computing/ |access-date=2022-03-23 |website=IONOS Digitalguide |language=en |archive-date=2022-01-28 |archive-url=https://web.archive.org/web/20220128110848/https://www.ionos.com/digitalguide/server/know-how/grid-computing/ |url-status=live }}</ref>

There are also some differences between programming for a supercomputer and programming for a grid computing system. It can be costly and difficult to write programs that can run in the environment of a supercomputer, which may have a custom operating system, or require the program to address [[Concurrency (computer science)|concurrency]] issues. If a problem can be adequately parallelized, a “thin” layer of “grid” infrastructure can allow conventional, standalone programs, given a different part of the same problem, to run on multiple machines. This makes it possible to write and debug on a single conventional machine and eliminates complications due to multiple instances of the same program running in the same shared [[computer memory|memory]] and storage space at the same time.