However, due to the insufficient support for sparse tensors from the current deep learning platforms, some of them have to represent a sparse matrix using a dense matrix with a binary mask or rely on customized CUDA kernels (Gray et al., 2017).
the speed-up or reduction in memory consumption is sometimes limited in practice.