We are two graduate Computer Science students at Columbia University interested in getting the most performance out of our deep learning models. For us this isn’t in terms of accuracy, but rather in terms of inference and training time and GPU efficiency. Our goal was to use gpu and cpu profilers to show how small changes to naive Deep Learning models can have significant impacts in training times.

You can find the source code for our project at: Project