DeepForge: A Machine Learning Gateway For Scientific Workflow Design
posterposted on 30.01.2020 by Brian Broll, Akos Ledeczi, Umesh Timalsina, Peter Volgyesi, Tamas Budavari
Poster sessions are particularly prominent at academic conferences. Posters are usually one frame of a powerpoint (or similar) presentation and are represented at full resolution to make them zoomable.
DeepForge is a gateway to deep learning for the scientific community. It provides an easy-to-use, yet powerful visual interface to facilitate the rapid development of deep learning models. This includes a carefully designed hybrid textual-visual programming interface to support novices as well as experts. Utilizing an extensible cloud-based infrastructure, DeepForge is designed to integrate with external compute and storage APIs to enable reuse of existing HPC resources including the SciServer from Johns Hopkins. The driving design principles are promoting reproducibility, ease of access, and enabling remote execution of machine learning pipelines. The tool currently supports TensorFlow/Keras, but its extensible architecture enables integrating additional platforms easily.