A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Personal experimentation with Deep-Q-Networks for reinforcement learning
A CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters.
Participation in the 2018 PLAsTiCC Astronomical Classification from Kaggle
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Transfer learning in tensorflow for Kaggle's challenge
Development repository for the Triton language and compiler