Weekly

Hi everyone, so this week has been comparatively more productive in terms of learning as well as work! I’m happy, so why not share with everyone as well? 🎉 PyTorch: (ft. Quansight and Facebook) Started working on porting index_add to structured kernels, see the PR I made on my forked repo here, and on upstream here. This included adding an out= variant to the op. Refining the way it’s registered in PyTorch. I am thinking to pass defalut value while registering, but it will be a BC breaking change. Finally got to use ghstack, thanks to Yukio (Quansight). Revised derivatives yaml file. Personally I feel that this one needs opinions from the Facebook team, and a lot of changes might be rejected (which is okay, at the end of the day - everything we do should be good for the library). My PR here is more like a prototype for everyone to get a chance to review, as well as comment on what they feel. Structured Kernel porting PR for baddbmm, bmm has been merged. Yay! 🎉 ❤️ PR. Took a walkthrough of lots of autogenerated code in PyTorch, to understand how ops are registered. Listened to Ed’s podcast - episode on NVIDIA GPUs. A sweet little introduction to NVIDIA GPUs. Extras: ...

Hi everyone, before I go ahead and share my progress, I wanted to quickly talk about what this blog is about. I am highly passionate with the idea of high performance computing, optimizing deep learning applications, and solving real world problems using deep learning, computer vision, and speech processing. While I’m on this path - I would like to document this somewhere. And while I’m doing that, why not share it publicly? ...