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Although such APIs may be fast (this is, after all, the purpose of a custom API), programs written using them may have to be substantially rewritten to function on a different machine. We do not consider APIs that were not designed for broad use. Automatic parallelization: Many compilers provide a flag, or option, for automatic program parallelization. When this is selected, the compiler analyzes the program, searching for independent sets of instructions, and in particular for loops whose iterations are independent of one another.

In some instances, the problem occurs only for a specific number of threads. As a result, a data race bug may escape detection during testing and even for some time when a program is in production use. Thus, the importance of avoiding this problem by paying careful attention during program development can not be overemphasized. Tools may help by pointing out potential problems. One can identify other potential causes of errors in OpenMP programs. For instance, if the programmer has relied on program execution by a certain number of threads and if a different number is used to execute the code, perhaps because insufficient resources are available, then results may be unexpected.

And, this may be the ticket to getting OpenMP to solve some very large problems on a very big machine. 6 11 The Bigger Picture Many kinds of computer architectures have been built that exploit parallelism [55]. In fact, parallel computing has been an indispensable technology in many cuttingedge disciplines for several decades. , Cyber205 [114], CRAY-1 [155], Fujitsu Facom VP-200 [135]). These systems dominated the high end of computing for several decades, and machines of this kind are still deployed.

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