EU funding for Deep Learning project

13 September 2017

UvA-scientist Andy Pimentel has received a grant of about €350.000 as partner of the ALOHA project. The purpose is to develop a software framework for runtime-Adaptive and secure Deep Learning On Heterogeneous Architectures.

Deep Learning algorithms are an extremely promising instrument in artificial intelligence, achieving very high performance in numerous recognition, identification, and classification tasks.

Adoption

To foster their pervasive adoption in a vast scope of new applications and markets, a step forward is needed towards the implementation of the on-line classification task (called inference) on low-power embedded systems, enabling a shift to the edge computing paradigm. Nevertheless, when DL is moved at the edge, severe performance requirements must coexist with tight constraints in terms of power/energy consumption, posing the need for parallel and energy-efficient heterogeneous computing platforms. 

Unfortunately, programming for this kind of architectures requires advanced skills and significant effort, also considering that Deep Learning algorithms are designed to improve precision, without considering the limitations of the device that will execute the inference. Thus, the deployment of Deep Learning algorithms on heterogeneous architectures is often unaffordable for SMEs and midcaps without adequate support from software development tools.

Goal

The main goal of ALOHA is to facilitate implementation of Deep Learning on heterogeneous low-energy computing platforms. To this aim, the project will develop a software development tool flow, automating:

  • algorithm design and analysis;
  • porting of the inference tasks to heterogeneous embedded architectures, with optimized mapping and scheduling;
  • implementation of middleware and primitives controlling the target platform, to optimize power and energy savings.

During the development of the ALOHA tool flow, several main features will be addressed, such as architecture-awareness (the features of the embedded architecture will be considered starting from the algorithm design), adaptivity, security, productivity, and extensibility. ALOHA will be assessed over three different use-cases, involving surveillance, smart industry automation, and medical application domains. 

Partners

The ALOHA consortium exits of fourteen partners, has a budget of six million euro's and will run from 2017 until 2021. Partners are: STMicroelectronics srl (IT), Università di Cagliari (IT), University of Amsterdam (NL), Leiden University (NL), ETH Zürich (CH), Università degli Studi di Sassari (IT), PKE Electronics AG (AT), CA Technologies Development Spain SA (ES), Software Competence Center Hagenberg GmbH (AT), Santer Reply Spa (IT), IBM israel - science and technology ltd (IL), Systhmata Ypologistikis Orashs Irida Labs ae (IT), Pluribus One srl (IT), MedyMatch Technology, ltd.(IL).

 

Published by  IVI