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in part 1 de-emphasise which means sacrifice as you stated I understand it reducing (de-emphasising) the maximisation of redundant computation... I am not able to understand reducing the minimization of redundant computation... kindly provide a little bit clarity

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Researcher: When writing code to perform a set of computations in a single sequential process, best practices dictate the minimization of redundant computations performed by the computer by using clever tricks to use the results of previous computations still in memory rather than starting each computation anew. In good multiprocess code, on the other hand, redundant computations are often performed in the interest of reducing the communication of results between processes. This allows the processes to complete the whole set of computations more quickly. In summary, good multiprocess coding deemphasizes the 1 in favor of emphasizing the 2
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De-emphasize 1: you don’t insist on minimizing every redundant computation and you're okay doing extra work.

Emphasize 2: your primary goal becomes minimizing the total elapsed time to complete the full set of computations.


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in part 1 de-emphasise which means sacrifice as you stated I understand it reducing (de-emphasising) the maximisation of redundant computation... I am not able to understand reducing the minimization of redundant computation... kindly provide a little bit clarity

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Researcher: When writing code to perform a set of computations in a single sequential process, best practices dictate the minimization of redundant computations performed by the computer by using clever tricks to use the results of previous computations still in memory rather than starting each computation anew. In good multiprocess code, on the other hand, redundant computations are often performed in the interest of reducing the communication of results between processes. This allows the processes to complete the whole set of computations more quickly. In summary, good multiprocess coding deemphasizes the 1 in favor of emphasizing the 2
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AnkurGMAT20
Researcher: When writing code to perform a set of computations in a single sequential process, best practices dictate the minimization of redundant computations performed by the computer by using clever tricks to use the results of previous computations still in memory rather than starting each computation anew. In good multiprocess code, on the other hand, redundant computations are often performed in the interest of reducing the communication of results between processes. This allows the processes to complete the whole set of computations more quickly. In summary, good multiprocess coding deemphasizes the 1 in favor of emphasizing the 2

We are given:

In good multiprocess code, on the other hand, redundant computations are often performed in the interest of reducing the communication of results between processes. This allows the processes to complete the whole set of computations more quickly.

So a good multiprocess code would perform calculation again instead of getting the result from a previous calculation because apparently, 'communicating the result' takes longer than 'recalculating the result.'

Hence good multiprocess coding deemphasizes "minimization of total number of computations performed." [color=#000000]They don't care if more computations are performed.[/color]
But emphasize the "minimization of total time to complete the set of computations." They do stress upon reducing the time taken to perform the batch of calculations.
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