> "Imagine being given a workstation with 1024 CPU cores, a terabyte of memory, and a GPU to match. Could you fully utilise this machine to solve everyday problems in your speciality? If not, why not? What are you missing?"

1. Shared memory space between the GPU and CPU

2. Tons of fast disk

Basically a memory hierarchy that descends from GPU RAM -> CPU cache/RAM -> fast hot storage (NVME) as easily as CPU cache/RAM or memory mapping works today.

Often that 1TB RAM is “wasted” with all of the copying required to feed things to the GPU in right-sized chunks.