Machine learning

Deep Learning Optimiser

This use case develops a deep learning optimiser that uses OmpSs to reduce the energy consumption of deep learning inference significantly. The optimiser makes use of OmpSs to increase the computational architectures supported by the optimiser to CPU, GPU and FPGA. The focus and aim is to facilitate the deployment of deep learning based AI on embedded systems for users in an energy- and cost-efficient manner.

LEGaTO enabled Machine Intelligence Sweden, one of its partners, to develop a Deep Learning Optimiser that has been spun out as its own company, EmbeDL. Furthermore, OmpSs@FPGA lowers the entry barrier for FPGA-development and has thus greatly improved the efficiency of the FPGA-development cycle.

Components

OmpSs@FPGA has been used to develop an FPGA implementation for deployment of deep neural networks.

LEGaTO components are available here: https://legato-project.eu/software/components

Scientific publications

• LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

Events

• AI4EU Web Café webinar, on 28 October 2020
• The Connector AI Digital Conference, on 9 June 2020
• MASA Day Digital, on 15 May 2020
• SSII AI, Big Data & XR Networking Conference, on 26 September 2019

LEGaTO: Machine Learning Use Case, presentation by Hans Salomonsson at the AI4EU Web Café webinar (28 October 2020)

News