A sled-dog kennel hears that training the photo-plus-log model “uses the GPU.” An intern offers to write a custom CUDA kernel “so training counts.” What is the correct associate stance?
Select an answer to reveal the explanation.
Short Explanation
Using the sled team’s engine is not the same as forging a new engine part for every run. Frameworks can put training on the GPU without anyone writing a kernel. Awareness of acceleration is enough at this level.
Full Explanation
GPU acceleration is typically provided through the deep-learning framework’s device support. Candidates should know training can use a GPU without treating custom CUDA kernel authorship as a requirement. This exam keeps CUDA at awareness depth for multimodal training workflows.