Month: April 2024

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NCC Montenegro and CIGRE organized successful HPC/AI Energy Workshop

NCC Montenegro, in collaboration with Montenegrin National Committee of CIGRE, one of the leading worldwide organizations on electric power systems, successfully organized a collaborative workshop, focusing on opportunities and benefits of HPC and AI complementary technologies in the energy sector, industry best practices and examples of high-fidelity energy metrics modelling. The workshop was attended by approx. 30 participants, academic researchers and industry experts, effectively converging HPC-powered AI research advancements with challenges and opportunities in the energy sector, driven by quality of predictive analytics and sustainability of energy models.

Representatives of HPC National Competence Centre of Montenegro, Sanja Nikolic and Luka Filipovic presented EUROCC2 project, NCC services, EuroHPC infractructure acces, PC4SME assessment tool and research, as well as success stories demonstrating advancements in HPC and AI applications in energy sector.

Mr Darko Krivokapić, Executive Director of the Directorate for Energy Management of the Montenegrin Electric Enterprise (EPCG), presented characteristics of Montenegro energy system and challenges of short- and long-term predictions of energy prices and consumption, depending on Montenegrin energy balance, renewable energy sources, weather conditions and trade dynamics/external risks facing electricity wholesale markets.

Mr Milutin Pavicevic PhD student@University of Donja Gorica and CEO of Alicorn, presented forecasting day-ahead electricity metrics (prices and loads) with different models of artificial neural networks and its accuracy comparison on the given dataset, elaborating on possible commercial implications in energy sector.

Mr Lazar Scekic, Teaching Assistant @University of Montenegro, introduced the audience with its research work on security challenges of electricity infrastructure (GPS spoofing) and reliable AI methods for the protection of electrical power systems against cyberattacks.

Mr Ivan Vujovic, PhD student @University of Belgrade and CEO of Tering, presented models related to prediction of production and consumption of electrical energy in the electrical system by using recurrent neural networks, discussing quality parameters that determine and improve predictive functioning of energy systems.

HPC and AI energy workshop enhanced awareness of NCC Montenegro services and EuroHPC infrastructure resources, available free of charge for the Montenegrin industry for the purpose of research, development and innovation.

Intensive discussion and exchange of opinions, expertise and experience between energy systems’ researchers and practitioners, including meteorological professionals also, open possibilities for the productive collaboration on calibrating computationally-demanding AI/ML models for national energy datasets, to improve their learning accuracy, prediction rates and potential of its commercial utilization in the energy system of Montenegro.

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Scientific paper at the 23rd INFOTEH-JAHORINA conference

A scientific paper “Output Manipulation via LoRA for Generative AI” by I. Culafic et al., was presented at the 23rd International Symposium INFOTEH-JAHORINA, 20-22 March 2024. The training for the prediction models was takin around six hours on an NVIDIA RTX 4090 24GB VRAM GPU. This research will serve as a basis for a future experiments on HPC resources. The paper is published at IEEE Xplore at: https://ieeexplore.ieee.org/document/10495995

ABSTRACT – Generative Artificial Intelligence has witnessed a surge in popularity in recent years, characterized by the emergence of groundbreaking models like DALL-E 2,
Midjourney, and Stable Diffusion, which have spearheaded advancements in this technological domain. This research aims to harness the potential of Stable Diffusion and its extensions for the purpose of training a LoRA (Low-Rank Adaptation) model to
generate images that closely resemble the original subject matter, utilizing a predetermined amount of example data. The primary objective of this research is to demonstrate the prowess of Stable Diffusion and generative AI in a broader context, delving into the possibilities offered by open-source frameworks, highlighting the
challenges associated with poorly organized training data and the advantages of properly organized and edited datasets, conducting a comparative analysis of diverse diffusion models and examining various LoRA strength examples. This research also aims to
compare the results from larger training parameters on both small and relatively large training models for the purpose of determining if overfitting, over training on one specific subject, is more prevalent with smaller or larger datasets.

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NCC MNE shared best practices @Industry Coffee Break

At the Industry Coffee Break on April 2nd, NCC representative Sanja Nikolic presented a concise overview of communication strategies, organizational efforts and NCCs and industry collaboration practices related to preparation of industry workshops in Montenegro, aimed to increase awareness on HPC/AI benefits, NCC services and EuroHPC infrastructure opportunities.

NCC Montenegro shared their strategic focus on cooperation with business associations, technology affiliations and industry clusters in organizing tailored HPC/AI workshops and steering companies’ interactions always keeping communication channels open and the collaboration model attractive (free NCC expertise and access to EuroHPC resources).

NCC Montenegro strongly supports international and interdisciplinary workshops to capitalize on the experience and expertise of the pan-European NCCs network, to heavily exploit EuroCC2 Success Stories, and to provide peer testimonials from companies already utilizing HPC resources to develop/optimize their AI models and promote business innovations.

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