it’s a rough measure but it’s right there
    start = time.monotonic()
    res = pool.map(init_process, [(i, size, run) for i in range(size)])
    end = time.monotonic()
    print(end - start)

then since in run i repeat 10 times i reason that i’m amortizing process instantiation across those 10 inference passes. and so between 1 and 4 GPUs end-start just grows.