What are the main challenges in data parallelism?
The main challenges in data parallelism include load balancing, communication overhead, and data dependency issues.
Can you explain load balancing in more detail?
Load balancing ensures that all processors have an equal amount of work. If one processor is overloaded while others are idle, it can lead to inefficiencies.
What about communication overhead?
Communication overhead refers to the time and resources spent on data exchange between processors, which can slow down overall performance.
How do data dependencies affect parallelism?
Data dependencies can create bottlenecks, as some tasks may need to wait for others to complete before they can proceed.
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