'How to handle receiving real time signals and passing signals into inference engine on Jetson Platforms

I am just looking for some advice on how to handle receiving a large number of signals in real time, storing these on a buffer and then passing the buffer to be processed by a inference engine/model on Jetson(l4t) platforms.

Currently I have something along the lines of

while True:
    for _ in read_x_times:
         temp_buffer = read_subset_of_samples_from_input_stream
         model_buffer[start:stop] = process(temp_buffer)
         if model_buffer_is_full:
             inference_engine.execute_v2(model_buffers)

The issue I have is that when the model_buffer is full and I call inference_engine, I am losing some samples from the input stream. The model_buffer lives on shared memory between the gpu and cpu.

What would be the best way to continue to receive samples while the model is processing the model_buffer.

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'How to handle receiving real time signals and passing signals into inference engine on Jetson Platforms

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