Having cutting-edge equipment is a pre-requisite to conduct high-quality research in the ICT domain (such as computing, robotics and sensoring or specialised audiovisual equipment).  During the 2 first years, almost 20% of the María de Maeztu funds have been used to finance equipment (163K EUR). The total upgrade of equipment directly linked to the development of the María de Maeztu program reaches 340KEUR, including additional funds provided by the department and the program by the Ministry of Economy and Competitiveness for scientific equipment and donations by the company NVIDIA of Graphic Processing Units.

COMPUTATION AND STORAGE

• High- performance computing: The core of this upgrade has been around the activity in the action ”A1.1. Equipment and supporting software” aimed to “develop a state-of-the-art data hosting and sharing infrastructure building on the existing equipment and technical staff and on the experience from running the existing computing infrastructures”. For this, the university launched a tender in 2016 and the system was in place, with a training session held in January 2018 and the final migration of services from the old HPC finalised in March 2018.
• Main page: http://hpc.s.upf.edu/ (it requires VPN for connections outside UPF Campus)
• User manual https://guiesbibtic.upf.edu/recerca/hpc/
• Monitoring system (accessible by Principal Investigators only http://intranet-rp.s.upf.edu )

• Workstation: Several research areas work with very large datasets (over 200GB, such as the case of synchrotron data or high-resolution microscopy) with very specific requirements for their computation and visualization, which cannot be met by the shared HPC. For this purpose, a new workstation (Dell Precision Tower 7910 XCTO) was acquired in 2016 and is currently hosted and used by BCN MedTech groups.

SMALL EQUIPMENT

• Robots (Transfer Perspectives Award, PhD Workshop 2018): Two Turtlebots were acquired as part of the Award obtained by Víctor Casamayor at the PhD Workshop 2018 and used in the context of the María de Maeztu project Knowledge Extraction for Retail (see blog entry)

• Sensors for psycho-physiological recordings: Set of sensors to capture reliable psycho-physiological data recordings within full-body interactive scenarios for work in the project Autism Spectrum Condition Multimodal Embodiment Open Repository (a specific blog entry on it soon to be published!)

• GPU Server (Reproducibility Award, PhD Workshop 2017: A GPU server was acquired by Jordi Pons as part of his award obtained at the PhD workshop 2017 to locally install two of the GPU cards donated by the company NVIDIA, to work on the training of deep learning models with TensorFlow, in the context of the project Machine learning approaches for structuring large sound and music collections (see blog entry). Although the current infrastructure perfectly suits their needs of cloud GPU computing, the team was also interested in trying different hardware solutions and, for that reason, built their own GPU server for training deep learning models with tensorflow

OTHER NEW FACILITIES AT DTIC-UPF

The MoCA Lab: a new Motion Capture and Analysis Lab at BCN MedTech

Although not direct part of the implementation of the María de Maeztu program, it is also worth mentioning the new MoCA Lab as it directly improves the capacities of the department to conduct data-driven research. The BCN MedTech research unit has launched the MoCA (Motion Capture and Analysis Lab) laboratory, within the framework of the project HOLOA – Clinical and virtual examination of patients for a holistic and objective description of the mechanisms of the progression of osteoarthritis (DPI2016-80283-C2-1-R). This lab uses a marker-based optical tracking technology and has been established at UPF by the Biomechanics and Mechanobiology area of BCN MedTech, with the cooperation of staff at  the Hospital del Mar Institute for Medical Research (IMIM), Barcelona. It is equipped with a system of eight infrared cameras with 1.5 MP resolution at 250 fps, and has the capacity to detect maker displacements inferior to 0.1 mm in an acquisition volume of 4x4x3 m3. The motion capture system is synchronised with video cameras and two force plates (additional information here)

Additional information:

Overview of the equipment and infrastructures available at the Department:

• Research infraestructures https://www.upf.edu/web/etic/research-infraestructures
• Educational infrastructures https://www.upf.edu/web/etic/educational_infrastructures