Partner MIS spun-off a new company, EmbeDL AB (
https://embedl.ai(odnośnik otworzy się w nowym oknie)) to commercialise the LEGaTO developed Deep Learning energy optimiser tool with the single focus on taking this technology to the market. The technology will be sold on a license based revenue model. EmbeDL AB completed the seed funding round to take the company's product to market with an initial focus on the automotive industry followed by IoT.
LEGaTO has developed several software packages and tools in the first phase of the project and ten of these packages have been made available for the public through the project Software Components portal at
https://legato-project.eu/software/components(odnośnik otworzy się w nowym oknie) and at the LEGaTO project github at
https://github.com/legato-project(odnośnik otworzy się w nowym oknie) The project has already demonstrated substantial decrease in energy consumption in the five use cases, based on the energy-efficient hardware platform and the task-based programming environment:
• The use of FPGAs resulted in a phenomenal 822x speedup in the healthcare use case, enabling a new world of biomarker analysis.
• The use of shared-memory programming style on distributed GPUs led to 10x energy savings in the smart home use case, the SmartMirror.
• The smart city use case on operational urban pollutant dispersion modelling had a 7x gain in energy efficiency thanks to the use of FPGAs and the OmpSs@FPGA programming environment.
• Up to 16x gain in energy efficiency and performance was achieved in the ML use case using the LEGaTO optimizer.
• The Secure IoT Gateway was vital to simplify the complexity of communication of local devices to a network, and it supported the above mentioned use cases to achieve their goals by reducing the complexity of security.
On the research side, partner BSC has decreased FPGA memory energy consumption by one order of magnitude through a technique termed undervolting; the results of this work appeared in the 51st Annual Symposium on Microarchitecture and were awarded a Tetramax technology transfer project to partners BSC and MIS.
The various elements of the software toolset have been integrated together to facilitate the porting of future use cases to the energy-efficient LEGaTO hardware/software platform. With regard to the work on hardware, a Cloud to Edge Microserver Platform was developed, which covers most of the domains from cloud, edge and embedded computing by using a microserver architecture and a scalable system. It includes the LEGaTO Edge Server, which was completely designed and built in the project and focuses on edge and embedded applications.
The results of the project were disseminated in many scientific papers, training courses, and events, and a final event was organised to present the project’s results. In addition, press releases were launched and technical news pieces were published regularly on the website, resulting in 27 press clippings and over 37,500 page views respectively. Two videos were produced to display the SmartMirror use case and the hardware developed in the project.
