PyTorch CUDA memory issue

[sminy67]

When I use a memory-intensive layers like embedding table of DLRM, I face with CUDA out of memory issue. So I came up with model-parallel which may be a solution for this issue.
But it looks like not a fundamental solution of this issue. So can I use the DRAM from CPU side as GPU memory and we only store the most frequently use embedding vectors to GPU?