no code implementations • 24 Mar 2020 • Nicolas Weber, Felipe Huici
In this paper we explore how to provide hardware support in AI frameworks without changing the framework's source code in order to minimize maintenance overhead.
no code implementations • 19 Oct 2018 • Nicolas Weber, Mathias Niepert, Felipe Huici
While the efficiency problem can be partially addressed with specialized hardware and its corresponding proprietary libraries, we believe that neural network acceleration should be transparent to the user and should support all hardware platforms and deep learning libraries.
no code implementations • 23 Apr 2018 • Nicolas Weber, Florian Schmidt, Mathias Niepert, Felipe Huici
Neural network frameworks such as PyTorch and TensorFlow are the workhorses of numerous machine learning applications ranging from object recognition to machine translation.
no code implementations • 2 Feb 2018 • Florian Schmidt, Mathias Niepert, Felipe Huici
Creating a model of a computer system that can be used for tasks such as predicting future resource usage and detecting anomalies is a challenging problem.
no code implementations • 10 May 2017 • Roberto Gonzalez, Filipe Manco, Alberto Garcia-Duran, Jose Mendes, Felipe Huici, Saverio Niccolini, Mathias Niepert
We present Net2Vec, a flexible high-performance platform that allows the execution of deep learning algorithms in the communication network.