KISS project goals
Deep learning allows solving problems that were considered unsolvable before. This is achieved by learning how to solve a problem from a set of training data. On the one hand, this requires solutions to efficiently create and process such training data. On the other hand, a major challenge today is how to determine efficient implementations of related multi-layer neuronal networks.
The KISS project aims to develop and offer methods and tools that help achieve these goals. More specifically, on the one hand it researches tools that generate better and more complete training data and allow for a more efficient training process. On the other hand, tools are developed to transform trained deep neuronal networks into an efficient implementation on different possible hardware architectures, including many-core processors (CPU), graphical processing units (GPUs) and field-programmable integrated circuits (FPGAs).