Artifact
Masa: Responsive Multi-DNN Inference on the Edge
Bart Cox (TU Delft - Data-Intensive Systems)
Jeroen Galjaard (Student TU Delft)
Amirmasoud Ghiassi (TU Delft - Data-Intensive Systems)
Robert Birke (ABB (Switzerland))
Lydia Y. Chen (TU Delft - Data-Intensive Systems)
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Abstract
This artifact is a guideline how the Edgecaffe framework, presented in [1], can be used. Edgecaffe is an open-source Deep Neural Network framework for efficient multi-network inference on edge devices. This framework enables the layer by layer execution and fine-grained control during inference of Deep Neural Networks. Edgecaffe is created to give more fine grained-control over the execution during inference than offered by the original code of Caffe [2]. Edgecaffe made it possible for Masa to outperform Deepeye [3] and normal bulk execution. Besides the core implementation of Edgecaffe, the repository holds additional tools, Queue Runner and ModelSplitter, that make more convenient to run experiments and prepare newly trained networks