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Optimizing multiprocessor systems

Nicholas Cravotta?? EDN特约技术编辑?? 2003年09月12日 ?? 收藏0
bstraction is, and the tools to accurately measure the cost are simply not available today.

The bottom line is that you can trade performance efficiency for the potential ease of design that comes through abstraction. You'll have your product up and running faster, but you'll also have to overprovide your design to accommodate all of the inefficiencies abstraction brings.

Ask yourself how much time to market costs you. And consider that 50% inefficiency in a six-processor system means you could
optimize down to five or four processors if you're willing to make the effort. The question is not whether the abstraction trade-off is worth making. You need to look at the real cost of abstraction on a case-by-case basis.


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Quantum math: 2.5+3.5=7

Instead of basing partitioning on function, try to partition on a smaller, more granular scale. For example, you might shoot for a performance quantum of 50 cycles, which becomes the currency of your time budget; every task should be some factor of 50 cycles, and tasks should be as close as possible to one or more than one quantum. Now, when you allocate cores, you can lump together several tasks into a single metatask. Say that you have partitioned two consecutive metatasks, such that you need to allocate 2.5 cores fo
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Optimizing? multiprocessor? communication?

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