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Answer: When the entire data can fit on each core
Increasing the number of cores from 4 to 8 can speed up the tuning process if the entire dataset can fit into the memory of each core. This allows each core to independently train a model simultaneously, effectively doubling the speed of the tuning process. However, if the data cannot fit into each core's memory, increasing the number of cores may lead to memory overflow, slowing down or even halting the process.
Author: LeetQuiz Editorial Team
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A machine learning engineer is looking to speed up a sluggish model tuning process by increasing the number of cores from 4 to 8, without adding more memory to the cluster. Under what conditions would this increase in cores actually accelerate the tuning process?
A
When the tuning process is randomized
B
When the model can't be parallelized
C
When the data has a lengthy shape
D
When the data has a broad shape
E
When the entire data can fit on each core
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