What are the differences between task and data parallelism?
An example of an AI chatbot conversation about the differences between task and data parallelism.
What are the differences between task and data parallelism?
Task parallelism involves distributing different tasks across multiple processors, while data parallelism involves distributing data across processors to perform the same task.
Can you give me an example of each?
Sure! In task parallelism, one processor might handle image processing while another handles data analysis. In data parallelism, all processors might work on different parts of a large dataset to compute the same function.
Which one is more efficient for large datasets?
Data parallelism is generally more efficient for large datasets because it allows simultaneous processing of data chunks, reducing overall computation time.
Are there any limitations to data parallelism?
Yes, data parallelism can be limited by factors like data dependencies, communication overhead between processors, and memory bandwidth.
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