Well, wrong. Computer scientists and electronic engineers had been experimenting with multi-processor computers with parallel programming since 1946. But it's not until the 1980's that we see the first parallel processing computers (built by Cray and other computer companies) being sold as commercial built computers. It's time for another example.
Example 24.4
The circus traveling by train from one city to the next has an elephant that dies. They decide to toss the elephant of the train (shame on them for trashing up the country side), but in short order a "super" ant (faster than most regular ants) fnds the elephant. This project is much larger than your tossed chicken bone. One single "super" ant could do the task (bite of a piece of the elephant and transport it to the colony, one bite at a time); but, it might take one whole year. After all this requires a lot more work than a chicken bone. But, what if he gets help? He signals some buddies and being a large colony of "super" ants they allocate a total of 2,190 ants to do the task. Wow, they devour the elephant in six hours.
This elephant example is exactly where the computer scientists had arrived. The electronic engineers were going to continue to make improvements in the speed of a single central processing unit computer, but not soon enough to satisfy the "need for power" to be able to solve tasks requiring immense computing power. Some of the new tasks that would require immense computer power included the human genome project, searching for oil and gas by creating 3 dimensional images of geological formations and the study of gravitational forces in the universe; just to mention a few. The solution: parallel processing to the rescue. Basically the only way to get this immense computer power was to implement parallel processing techniques. During the late 1970's and early 1980's scientists saw the need to explore the parallel processing paradigm more fully and thus the birth of High Performance Computing. Various national and international conferences started during the 1980's to be able to further the cause of High Performance Computing. For example in November of 2008 the "SC08" supercomputing conference celebrated their 20th anniversary.
The predicting of the weather is a good example for the need of High Performance Computing. Using the fastest central processing unit computer it might take a year to predict tomorrow's weather. The information would be correct but 365 days late. Using parallel processing techniques and a powerful "high performance computer", we might be able to predict tomorrow's weather in 6 hours. Not only correct, but in time to be useful.
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