NVIDIA / apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
BSD 3-Clause "New" or "Revised" License
8.44k stars 1.41k forks source link

[contrib/ASP] Question about Sparsity performance use case #993

Open sakaia opened 4 years ago

sakaia commented 4 years ago

I am trying to run ASP toy_problem.py. It seems nothing changes. Is there any method for seeing performance gain?

I am comparing train_loop/arg.num_xxx_steps for dense and sparse. It seems few percentage changes.

Another document for sparsity says, 50% performance gain on BERT (on MLPerf). But toy_problem.py seems no effect for sparsity. Of course BERT uses TensorRT for MLPerf, I understand software interface is different.

References

calclavia commented 3 years ago

Seems like the acceleration doesn't work from this code base - since there's no kernel implemented: https://github.com/NVIDIA/apex/blob/master/apex/contrib/sparsity/sparse_masklib.py#L57

rg321 commented 1 year ago

Are you using Ampere architecuture? I suppose sparsity works for Ampere architectures for now