National Competence Centre for High-Performance Computing
MAIA – Montenegrin AI Association is a Non-Governmental organization, founded in September 2022 with an ambition to bring together the Montenegrin AI community. Our goal is to popularize Artificial Intelligence related research and spread awareness of its importance in our country, but also encourage our society to join the fast wave of AI innovation in the World. Several NCC Montenegro team members are taking part in this initiative. Check MAIA website for more details at the following link.
A hosting agreement has been signed between the EuroHPC Joint Undertaking and the National Infrastructures for Research and Technology (GRNET) in Greece where DAEDALUS, a new EuroHPC supercomputer will be located. University of Donja Gorica is one of the partners in the implementation of the project.
Once procured, DAEDALUS will be a mid-range supercomputer, able to perform more than 30 petaflops or 30 million billion calculations per second. This new supercomputer will be managed and operated by GRNET, the National Infrastructures for Research and Technology in Greece. DAEDALUS will be installed in the historical 19th century Electric Power Station building in Lavrion Technological and Cultural Park and is expected to have an overall surface area of 1500 m2.
The supercomputer will power new applications in a wide range of areas, such as engineering, chemistry, health sciences and will be used to visualise and solve scientific problems. It will advance science and boost the innovation potential of enterprises while improving the European citizens’ quality of life.
DAEDALUS, at a total acquisition cost of EUR 33 million, will be co-funded with a maximum total budget of up to EUR 10 million by the EuroHPC JU (35%) and Greece (65% of national funds). Cyprus, Montenegro and North Macedonia are also involved in the project as members of the DAEDALUS consortium. This partnership is strategic for the European Union as it will support science and technology in the wider area of South-East Europe.
DAEDALUS Partners:
Links for more details:
Researchers from UDG and NCC Montenegro presented a scientific paper at the 2022 International Arab Conference on Information Technology (ACIT). The conference took place at the Al Ain University – Abu Dhabi Campus on November 22-24, 2022. The paper “Overcoming Limitations of Statistical Methods with Artificial Neural Networks” was authored by M. Grebovic, L. Filipovic, I. Katnic, M. Vukotic, and T. Popovic. More information about the conference is available here. The paper is available at IEEE Xplore at the following link.
ABSTRACT – Traditional statistical models as tools for summarizing patterns and regularities in observed data can be used for making predictions. However, statistical prediction models contain small number of important predictors, which means limited informative capability. Also, predictive statistical models that provide some type of pseudo-correct regular statistical patterns, are used without previous understanding of the used data causality. Machine Learning (ML) algorithms as area in Artificial Intelligence (AI) provide the ability to interpret and understand data in more sophisticated way. Artificial Neural Networks as kind of ML methods use non-linear algorithms, considering links and associations between parameters, while statistical use one-step-ahead linear processes to improve only short-term prediction’s accuracy by minimizing cost function. Disregarding that designing an optimal artificial neural network is very complex process, they are considered as potential solution for overcoming main flaws of statistical prediction models. However, they will not automatically improve predictions accuracy, so several artificial neural networks and traditional statistical methods are evaluated and analyzed through accuracy measures for prediction purposes in various fields of applications. Based on gained results, couple of techniques for improving artificial neural networks are proposed to get better accuracy results than statistical predictive methods.
AIMHiGH project, a FF4EuroHPC application experiment, was presented at the SmAgTech EXPO2022. Mr Stevan Cakic gave a presentation at the conference during the plenary sessions on 24 Nov 2022. AIMHIGH was also featured in the virtual EXPO platform in the Projects section.
Deep learning and HPC training organized by NCC Montenegro and UDG is featured in the national news portal CDM. The presentations and guest talks will be accessible to students and academia, industry, and general public. There is a very interesting line up of lecturers coming from reputable institutions from the region and abroad. More information about the training is available here. Click on the image below to open the post at the CDM news portal.
The AIMHiGH project, a FF4EuroHPC application experiment for development of computer vision solutions for smart poultry farms, can be seen in the background at the SC22 (#SC22) exhibition booth for FF4EuroHPC during the International Conference on High Performance Computing, Storage and Analysis (Dallas, Texas). AIMHiGH was featured as one of the success stories of the FF4EuroHPC project. Learn more about the FF4EuroHPC project and check out the success stories at the following link.
University of Donja Gorica, NCC Montenegro and NCC Spain are organizing course “Deep Learning and HPC”. During this course, students will learn how to implement deep learning models for real applications on local machines, key mathematical concepts of deep learning, some key concepts about computer vision and natural language processing. n the second part of training, students will be familiarized to high-performance computing in deep learning application development, parallel computing with Python on multiple CPUs or GPUs, pyTorch library for developing deep learning models.
The talks from visiting lecturers start on 30 November, so it is needed to express your interest as soon as possible. Course is open to academia, industry and public sector. Link for online registration is available here.
Recommended requirements and background:
The Agenda is now available at the following link.
