LINKS Foundation

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The LINKS Foundation was founded in 2016 exploiting and enhancing the experience gained - from the Istituto Superiore Mario Boella (ISMB) and from the Istituto Superiore on Territorial Systems for Innovation (SiTI) - in the first 2 decades of the new millennium in the field of research applied and technology transfer, adding a fundamental element such as the enhancement of the research result. As part of the knowledge chain, the Foundation intends to enhance the lever of applied research, contributing to the growth of the socio-economic system by relating the academic world, the public and private sectors, activating large-scale processes and projects with significant impacts on territory. The Foundation intends to establish a dialogue with the local, national and international business entrepreneurship, in order to share and enhance knowledge, experience and innovation.

The Foundation is an ideal partner for both SMEs, which can enhance the ability to develop innovation and gain competitiveness using the experience and expertise of the foundation, both of the Large Enterprises that can, in partnership with it, develop new ideas and new technologies. The Foundation today relies on the technological and process competences of around 150 researchers working in close cooperation with companies, academia and public administration. LINKS operates according to the knowledge management model: this means that it plays an active role not only in devising innovative solutions, but also in their implementation and consequent developments. This approach represents a step forward with respect to technology transfer, and in this sense the evolutionary lines of European research are taken into account. LINKS is organized in Research Areas focused on some core sectors of ICT. Within the field of HPC systems, LINKS is active in two main topics:

 

 

 

 

 

1) applied research activities in Advanced Computing with: the study and design of distributed computing architectures based on public and private cloud platforms like AWS and OpenStack; low power architectures in high performance perspective; orchestration of heterogeneous architectures in computing continuum; resources and applications management in distributed environment; application analysis, design and development for machine learning, HPC-embedded context through many-core architecture

2) applied research in Data Science for extreme scale analysis of Big Data, including: the design of distributed databases and processing architectures for heterogeneous types of data; the development of distributed Data Mining and Machine Learning algorithms for different applications.

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