Pytorch has its function torch.qr() to implement QR decomposition. For instance, let A be a matrix with size of 3000*60. I have installed Magma as LAPACK support. If I place A on CPU by A.cpu(), to compute torch.qr(A) for 100 times, it will take about 0.4 second. However, when I place A on GPU by A.cuda(), it will take 1.4 seconds. I thought running on GPU should be faster than running on CPU. Can anyone explain this phenomenon to me? Thanks a lot!