What is model parallelism in AI?
Model parallelism is a technique where different parts of a model are run on different devices to improve performance.
Can you give me an example of how model parallelism is used?
Sure! In large neural networks, different layers can be distributed across multiple GPUs to speed up training.
What are the benefits of using model parallelism?
The main benefits include faster training times, the ability to handle larger models, and efficient resource utilization.
Are there any challenges with model parallelism?
Yes, challenges include increased complexity in model management and potential communication overhead between devices.
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