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Q. Explain Time Complexity in Parallel algorithms?
As it takes place nearly everyone who implement algorithms wish to know how much of an individual resource (for example time or storage) is needed for a given algorithm. The parallel architectures have been intended for improving computation power of several algorithms. So the main concern of evaluating an algorithm is the determination of amount of time needed to execute. Generally the time complexity is computed on the grounds of total number of steps implemented to achieve the desired output.
The Parallel algorithms generally divide the problem in more asymmetrical or symmetrical sub problems and shift them to various processors and put results back together at one end. The resource utilization in concurrent algorithms is both the communication overhead between the processors and also processor cycles on each processor.
The Task Gantt shows the various tasks being performed i.e., some type of activities by the set of processors attached to the parallel computer as shown in Figure . Task Gantt
Explain Priority encoder with an example. Ans. Priority encoder- Basically an encoder is a combinational circuit which performs the inverse operation of a decoder. The inp
Capacity: Raw capacity Total amount of stored information that a medium or storage device can hold is expressed as a quantity of bytes and bits (for example 10.4 megabyte
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Data Validation condition: The following condition stated below must be met for a data to be valid as is shown in the figure 3a below. 1. The data on the SDA line must remain stabl
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a luminous jewel game c programming start with t and end with t the output will yes or no
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