Introduction To Parallel Processing Algorithms And by Parhami

By Parhami

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Moore’s revised prediction matches almost perfectly the actual increases in the number of transistors in DRAM and microprocessor chips. Moore’s law seems to hold regardless of how one measures processor performance: counting the number of executed instructions per second (IPS), counting the number of floating-point operations per second (FLOPS), or using sophisticated benchmark suites that attempt to measure the processor's performance on real applications. This is because all of these measures, though numerically different, tend to rise at roughly the same rate.

Let us consider first a special case of semigroup computation, namely, that of maximum finding. Each of the p processors holds a value initially and our goal is for every processor to know the largest of these values. A local variable, max-thus-far, can be initialized to the processor’s own data value. In each step, a processor sends its max-thus-far value to its two neighbors. , max(left, own, right). 6 depicts the execution of this algorithm for p = 9 processors. The dotted lines in Fig. 6 show how the maximum value propagates from P6 to all other processors.

Even though it is expected that Moore's law will continue to hold for the near future, there is a limit that will eventually be reached. That some previous predictions about when the limit will be reached have proven wrong does not alter the fact that a limit, dictated by physical laws, does exist. The most easily understood physical limit is that imposed by the finite speed of signal propagation along a wire. This is sometimes referred to as the speed-of-light argument (or limit), explained as follows.

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