Deep Learning in Edge Computing Platforms. ALOHA tutorial at HIPEAC 2020. Registration available


The HiPEAC conference (High Performance and Embedded Architecture and Compilation) is a prestigious annual European forum for experts in computer architecture, programming models, compilers and operating systems for embedded and general-purpose systems. The HiPEAC 2020 conference will take place in Bologna, Italy (Polo congressuale). Associated workshops, tutorials, special sessions, several large poster session and an industrial exhibition will run in parallel with the conference.

The ALOHA consortium will held a tutorial during HiPEAC 2020, on January 21th, SALA AVORIO (from 2:00 p.m. to 5:30 p.m.). The tutorial is meant to offer an overview how to use the ALOHA framework and its different functionalities.

Paolo Meloni, Università degli Studi di Cagliari
Francesca Palumbo, Università degli Studi di Sassari
Francesco Conti, ETH Zurich

Title of the turorial: Deep Learning in Edge Computing Platforms: the ALOHA framework

Abstract of the tutorial:
Deep Learning (DL) algorithms are an extremely promising instrument in artificial intelligence. To foster their adoption in new applications and markets, a step forward is needed towards the implementation of DL inference on low-power embedded systems, enabling a shift to the edge computing paradigm. The H2020 ALOHA project started in January 2018, and aims at facilitating implementation of DL algorithms on heterogeneous low-energy computing platforms providing automation for optimal algorithm selection, resource allocation and deployment. The outcome of the project is a framework for the automatic cross-optimization and porting of DL algorithms over different embedded computing platforms, ranging from commercial micro-processors, like SensorTile, to more advanced heterogeneous computing platforms as the STMicroelectronics Orlando (a low-power IoT end-nodes integrating specialized hardware blocks for specific compute-intensive data processing) or NEURAghe (a Zynq-based heterogeneous architecture accelerating convolutional neural networks).

Official page and registrations:


Project Coordinator
Giuseppe Desoli - STMicroelectronics

Scientific Coordinator
Paolo Meloni - University of Cagliari, EOLAB

Dissemination Manager
Francesca Palumbo - University of Sassari, IDEA Lab