Thank you for the quick reply. As you can see it greatly mirrors the other post.
import torch

ngpu = torch.cuda.device_count()
# This is the allocation to each GPU.
lis = []
for i in range(ngpu):
    lis.append(torch.rand(5000,5000,device = 'cuda:'+ str(i)))

# per the matmul on multiple GPUs post this should already be in parallel to my understanding
# but doesnt seem to be based on watch nvidia-smi
C_ = []
for i in range(ngpu):
    C_.append(torch.inverse(lis[i]))