TensorFlow is an open-source machine learning system, originally developed by the Google Brain team, which operates at large scale and in heterogeneous environments. TensorFlow trains and executes a variety of machine learning models at Google, including deep neural networks for image recognition and machine translation. The system uses dataflow graphs to represent stateful computations, and achieves high performance by mapping these graphs across clusters of machines containing multi-core CPUs, general-purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). In this talk, I will give a brief overview of how TensorFlow was designed, and how it differs from contemporary systems. I will also highlight the opportunities for future systems research on top of TensorFlow.

Bio:
Derek Murray is a Software Engineer in the Google Brain team, working on TensorFlow. Previously, he was a researcher at Microsoft Research Silicon Valley where he worked on the Naiad project, and he received his PhD in Computer Science from the University of Cambridge.

More Info: http://www.pdl.cmu.edu/SDI/2017/040617.html