C3S@UNITO will use INDIGO software tools

Adopting INDIGO-Data Cloud: the Scientific Computing Competence Centre of the University of Torino will use INDIGO software tools

The INDIGO-Data Cloud project is happy to announce that it signed a Memorandum of Understanding (MoU) with the Scientific Computing Competence Centre of the University of Torino (C3S).

A Memorandum of Understanding has just been signed.

The INDIGO-Data Cloud project is happy to announce that it signed a Memorandum of Understanding (MoU) with the Scientific Computing Competence Centre of the University of Torino (C3S). C3S is a research centre that focuses on scientific computing technology and applications and manages OCCAM, • Open Computing Cluster for Advanced data Manipulation • a multipurpose HPC Cluster. Thanks to this agreement, a collaboration has been set-up between C3S and the INDIGO-DataCloud project for the use and development of advanced tools for scientific computing, particularly for heterogeneous use-case management in an HPC infrastructure context.

C3S will have access to software tools developed by INDIGO-DataCloud and will be able to integrate them in the management layer of the OCCAM supercomputer. The INDIGO teams collaborate with C3S in adapting and porting the tools to the specific use cases, giving support on a best-effort basis and providing, whenever feasible, patches and customisations for its software products.

“INDIGO-DataCloud aims at providing services that can be deployed on different computing platforms and enable the interoperability of heterogeneous e-infrastructures. C3S is a very interesting opportunity to test such capabilities and prove how our tools can really make the difference, providing seamless access, elasticity and scalability for the exploitation of data and computational resources” • says Giacinto Donvito, the Technical Director of the INDIGO-DataCloud Project.

“We have a very wide variety of use cases, from traditional HPC in computational chemistry, physics and astrophysics to data-intensive genomics and computational biology all the way to social sciences and even the humanities, so we will have to use the best tools to accommodate them all. We trust that many INDIGO products will help us to improve the performance and usability of our centre” says Matteo Sereno, professor at the Department of Computer Science of the University of Torino and C3S Director.

http://cordis.europa.eu/news/rcn/138515_en.html

Technical information in:

M. Aldinucci, S. Bagnasco, S. Lusso, P. Pasteris, S. Vallero, and S. Rabellino, “The Open Computing Cluster for Advanced data Manipulation (OCCAM),” in The 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP), San Francisco, USA, 2016.

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About Marco Aldinucci

Marco Aldinucci is an assistant professor at Computer Science Department of the University of Torino since 2008. Previously, he has been researcher at University of Pisa and Italian National Research Agency. He is the author of over a hundred papers in international journals and conference proceeding (Google scholar h-index 21). He has been participating in over 20 national and international research projects concerning parallel and autonomic computing. He is the recipient of the HPC Advisory Council University Award 2011 and the NVidia Research award 2013. He has been leading the “Low-Level Virtualization and Platform-Specific Deployment” workpackage within the EU-STREP FP7 ParaPhrase (Parallel Patterns for Adaptive Heterogeneous Multicore Systems) project, the GPGPU workpackage within the IMPACT project (Innovative Methods for Particle Colliders at the Terascale), and he is the contact person for University of Torino for the European Network of Excellence on High Performance and Embedded Architecture and Compilation. In the last year he delivered 5 invited talks in international workshops (March 2012 – March 2013). He co-designed, together with Massimo Torquati, the FastFlow programming framework and several other programming frameworks and libraries for parallel computing. His research is focused on parallel and distributed computing.