Write in details about issue of “Obtaining fine granularity timers”.
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Answer:
In parallel computing, granularity (or grain size) of a task is a measure of the amount of work (or computation) which is performed by that task.[1]
Another definition of granularity takes into account the communication overhead between multiple processors or processing elements. It defines granularity as the ratio of computation time to communication time, wherein, computation time is the time required to perform the computation of a task and communication time is the time required to exchange data between processors.[2]
If {\displaystyle T_{\mathrm {comp} }}{\displaystyle T_{\mathrm {comp} }} is the computation time and {\displaystyle T_{\mathrm {comm} }}{\displaystyle T_{\mathrm {comm} }} denotes the communication time, then the Granularity G of a task can be calculated as:[2]
{\displaystyle G={\frac {T_{\mathrm {comp} }}{T_{\mathrm {comm} }}}}{\displaystyle G={\frac {T_{\mathrm {comp} }}{T_{\mathrm {comm} }}}}
Granularity is usually measured in terms of the number of instructions executed in a particular task.[1] Alternately, granularity can also be specified in terms of the execution time of a program, combining the computation time and communication time.[1]
Explanation:
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