Explanation:
A common reason for underutilized TPUs is a small batch size. TPUs are designed for high throughput, and feeding them small batches doesn't leverage their full potential. Increasing the batch size allows the TPU to process more data concurrently, thus better utilizing its capacity and speeding up the training process.
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You are training an ML model on a large dataset using Tensor Processing Units (TPUs) to accelerate the training process. Despite this, you notice that the training is taking longer than expected. Upon investigation, you discover that the TPU is not being fully utilized, with its capacity not reaching optimal levels. What adjustment should you make to improve TPU utilization and speed up the training process?
A
Increase the learning rate
B
Increase the number of epochs
C
Decrease the learning rate
D
Increase the batch size