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Who is familiar with the best practices for data-driven task-level parallelism using only hls::stream objects? When writing a streaming function, I am unsure if I should use an infinite loop to read from the input stream whenever data is available. I seek a professional explanation to ensure my code is both scalable and very efficient.

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