Download Algorithms and parallel computing by Fayez Gebali PDF

By Fayez Gebali

There's a software program hole among the strength and the functionality that may be attained utilizing todays software program parallel software improvement instruments. The instruments want handbook intervention by means of the programmer to parallelize the code. Programming a parallel laptop calls for heavily learning the objective set of rules or program, extra so than within the conventional sequential programming we've got all realized. The programmer has to be conscious of the conversation and information dependencies of the set of rules or program. This publication presents the concepts to discover the potential how one can application a parallel laptop for a given program.

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Consider the speedup factor for a fully parallel algorithm when communication overhead is assumed. Comment on speedup for possible values of R. 15. Write down the speedup formula when communication overhead is included and the algorithm requires interprocessor communications Assume that each task in the parallel algorithm requires communication between a pair of processors. Assume that the processors need to communicate with each other m times to complete the algorithm. 16. Consider an SPA with the following specifications: Number of serial tasks per stage Number of serial tasks per stage Number of stages Ns Np n Now assume that we have a single processor that requires τ to complete a task and it consumes W watts while in operation.

The type of gate circuits also dictate the clock speed, such as using CMOS or domino logic or current-mode logic. There is also a fundamental limit on how fast a chip could run based on dynamic power dissipation. 1) where C is the total parasitic capacitance, f is the clock frequency, and V is the power supply voltage. Engineers developed many techniques to reduce power consumption of the chip while raising the clock frequency. One obvious solution was to reduce the value of C through finer lithographic process resolution.

5. We note from the figure that speedup is affected by the value of f. As expected, larger f results in more speedup. 5. Another observation is that speedup saturates to a given value when N becomes large. For large values of N, the speedup in Eq. 23 is approximated by S( N ) ≈ 1 1− f when N 1. 25) This result indicates that if we are using a system with more than 10 processors, then any speedup advantage is dictated mainly by how clever we are at discovering the parallel parts of the program and how much we are able to execute those parallel parts simultaneously.

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