Could I ask you a question?
I trained a network and then used this network to process the image sequence and the Caffe framework is adopted. When I started one task, GPU load is 65%, but when I ran two independent tasks at the same time, the GPU load is only 70%. The processing speed of each road is almost half that of the original, that is, it cost two times time to process each task. The utilization rate of CPU is not high and there is plenty of memory. And there are no other tasks taking up GPU. My GPU is not full but processing speed is down,do you know why?
Could I ask you a question? I trained a network and then used this network to process the image sequence and the Caffe framework is adopted. When I started one task, GPU load is 65%, but when I ran two independent tasks at the same time, the GPU load is only 70%. The processing speed of each road is almost half that of the original, that is, it cost two times time to process each task. The utilization rate of CPU is not high and there is plenty of memory. And there are no other tasks taking up GPU. My GPU is not full but processing speed is down,do you know why?