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InfluxDB
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Likely areas for parallelisation depend on the operations that are happening - if there are independent stages then they can often be made to run at the same time in separate threads (or processes). Concurrency is similar, although more about doing something else while waiting for I/O, and can generally be solved with threads or asyncio coroutines. A common improvement for video-focused computer vision pipelines is reading in/capturing the next frame while the previous frame is being processed (e.g. like is done with pythonic-cv - disclaimer: my library), but given the frame rates you specified then that may help a bit but is likely not the main culprit. ML-based algorithms can often benefit from the inherent parallelisation of a GPU-based implementation, although that can be difficult or even impossible to achieve depending on the algorithm being used.
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