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We could either optimize every last scintilla of performance out of one of those machines or we could get lots of them working on the data in parallel. The former route costs us lots of time and money in terms of labor costs (developers) and capital costs for a small number of top-of-the-range computers. Also, the outcome of the investment in terms of improved throughput is uncertain. The latter route - lots and lots of cheap "throwaway" machines - will cost us a fixed amount of money (low labor costs as we are not optimizing any algorithms) and we can accurately measure the improvements in throughput we expect to see. Sean McGrath

February 4, 2004 12:36 AM

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