The schedule is tentative and can subject to change. We will have guest lectures and may accomodate the schedule accordingly.

Mar 27th Introduction to Deep Learning
Mar 29th Lab: How to build image classifier
April 3th Components Overview of Deep Learning System
April 5th Backprop and Automatic Differentiation
April 10th Hardware backends: GPU
April 12th Optimize for hardware backends
April 17th Domain specific language, TVM
April 19th Programming your Accelerators with DSL
April 24th Computation graph: memory optimization
April 26th Parallel Scheduling
May 1st TBD
May 3rd TBD
May 8th TBD
May 10th Distributed Training and Communication Primitives
May 15th Case Study of Existing Deep Learning Systems
May 17th Model Serving Systems
May 22nd TBD
May 24th TBD
May 29th TBD
May 31st TBD
June 5th Project Presentations