What are the main challenges of parallel machine learning?
An example of an AI chatbot conversation about the challenges in parallel machine learning.
What are the main challenges of parallel machine learning?
Some key challenges include data synchronization, load balancing, and communication overhead between nodes.
Can you explain data synchronization in more detail?
Data synchronization ensures that all parallel processes have access to the same data state, which can be complex.
What about load balancing? Why is it important?
Load balancing is crucial to ensure that all processors are utilized efficiently, preventing some from being overworked while others are idle.
How does communication overhead affect performance?
Communication overhead can slow down processing as it takes time for data to be transferred between nodes, impacting overall efficiency.
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