In the past half century, parallel computers, parallel computation,

and scientific research have grown up together. Scientists

and researchers’ insatiable need to perform more and larger

computations has long exceeded the capabilities of conventional

computers. The only approach that has met this need is

parallelism—computing more than one operation simultaneously.

At one level, parallelism is simple and easy to put into practice.

Building a parallel computer by replicating key operating components

such as the arithmetic units or even complete processors is

not difficult. But it is far more challenging to build a well-balanced

machine that is not stymied by internal bottlenecks. In the end,

the principal problem has been software, not hardware. Parallel

programs are far more difficult to design, write, debug, and tune

than sequential software—which itself is still not a mature, reproducible

artifact.

Publisher  Microsoft Research
© 2009 Microsoft Corporation. All rights reserved.

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