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Deep Learning on GPU

原文 2018-11-14 17:41:04 2 0 docker/ tensorflow/ nvidia/ gpu-programming/ nvidia-docker

A DGX-1 has quite a lot of power. However, when using it I only utilize 34% of one of eight cards. Are there some points and tweaks I might missed? I know I can't parallelize everything, there is an upper limit. But to be honest, I expected a better performance.

I'm running a nvidia-docker with tensorflow preinstalled. The script running is from dennybritz which is quite well used. I ran the docker one one card. Since it didn't utilized the whole card I didn't gave him second one. Would this have any benefit? Of course I could ran multiple instances and pick the best one. But I'd rather have results sooner when having 170TFLOPS accessible.

0 answers

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