A small startup is developing a model to classify customer reviews as positive or negative. Their dataset contains 50,000 reviews, and the model architecture is simple enough to be trained on a single high-end graphics card in under three hours. The lead engineer decides to spend a week configuring a system to train the model across ten separate machines, arguing it will accelerate the process. Evaluate the engineer's decision. Is this an effective use of resources? Justify your answer by explaining the primary trade-offs involved in using a multi-processor approach.