[my123]

CUDA provides a tier significantly above that: unified memory.

See: https://on-demand.gputechconf.com/gtc/2017/presentation/s728...

And: https://docs.nvidia.com/cuda/cuda-c-programming-guide/index....

However, the Windows driver infrastructure's unified memory support is much further behind, with the pre-Pascal feature set.

For those you'll have to use Linux. Note that WSL2 is considered as Windows for this, it's a driver infrastructure limitation in Windows.

[andoma]

I've switched to using cudaMallocManaged() exclusively. From what I can tell there's isn't much of a performance difference. A few cudaMemPrefetchAsync() at strategic places will remedy any performance problems. I really love the ability that you can just break with gdb and look around in that memory as well.

[einpoklum]

Unified memory is just _different_, not above or below. It offers on-demand paging. But that comes at a cost (at times) in terms of memory I/O speed.

[my123]

It's a feature tier above, with much more emphasis on ease of use from the programmer's perspective.

It also allows for significantly more approachable programming models. For example: https://developer.nvidia.com/blog/accelerating-standard-c-wi...