Q: 2
A healthcare company is training a large convolutional neural network (CNN) for medical image
analysis. The dataset is enormous, and training is taking longer than expected. The team needs to
speed up the training process by distributing the workload across multiple GPUs and nodes. Which of
the following NVIDIA solutions will help them achieve optimal performance?
Options
Discussion
Pretty clear it's B
Pretty sure B here. NCCL handles communication across multiple GPUs and nodes, and DALI speeds up the data pipeline so you aren't waiting on I/O. I've seen similar training questions recommend both in practice tests. Official NVIDIA docs or hands-on labs could help if anyone wants to dig deeper. Agree?
B tbh, seen similar advice in the official NVIDIA guide and practice exams for multi-node CNN training.
Its B
I don't think it's A. B is better for distributed multi-GPU training, cuDNN is mostly single GPU.
Probably A. cuDNN is usually what speeds up CNNs specifically, so I’d think that would be the go-to for making training faster with NVIDIA hardware.
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