Sure. Make sure you publish the paper and ping me here again once the code is public. 
PS: Not sure, if you’re already using it, but add torch.backends.cudnn.benchmark = True at the beginning of your script. This will run benchmarks for each new input shape and select the fastest cudnn kernel for your workload. Note that the first iteration will be slower due to benchmarking (and each “first” iteration for new input shapes).