NICOLAS WEBER

My main research interests are the automated optimization of code running on accelerator hardware, especially for Scientific and High Performance Computing, Biomedical and Artificial Intelligence applications. During my PhD I developed MATOG, an automated tool that automatically chooses optimal memory access patterns in CUDA applications. Since I joined NEC Labs I mainly worked on the SOL project. SOL is a compiler for neural networks running in PyTorch, TensorFlow or ONNX. It has many similarities with TVM, but in contrast mainly focusses on training, therefore provides it's own AutoGrad implementation and much tighter integration into the executing frameworks... Researching Automatic Performance Optimizations for Artificial Intelligence, Scientific and High Performance Computing

Primary location: Heidelberg Germany