RAM size

As we saw previously in this section, most of the deep learning applications read directly from RAM instead of CPU caches. Hence, it is often advisable to keep the CPU RAM almost as large, if not larger, than GPU RAM.

The size of the GPU RAM depends on the size of your deep learning model. For example, ImageNet based deep learnings models have a large number of parameters taking 4 GB to 5 GB of space, hence a GPU with at least 6 GB of RAM would be an ideal fit for such applications. Paired with a CPU with at least 8 GB or preferably more CPU RAM will allow application developers to focus on key aspects of their application instead of debugging RAM performance issues.