Where I work, we do a lot of numerical computations and we are considering buying workstations with NVIDIA video cards because of CUDA (to work with TensorFlow and Theano).
My question is: should these computers come with another video card to handle the display and free the NVIDIA for the GPGPU?
I would appreciate if anyone knows of hard data on using a video card for display and GPGPU at the same time.
In my experience it is awkward to share a GPU card between numerical computation tasks and driving a video monitor. For example, there is limited memory available on any GPU, which is often the limiting factor in the size of a model you can train. Unless you're doing gaming, a fairly modest GPU is probably adequate to drive the video. But for serious ML work you will probably want a high-performance card. Where I work (Google) we typically put two GPUs in desk-side machines when one is to be used for numerical computation.