N-Ways to GPU Programming Bootcamp

The NVIDIAEuroCC AustriaEuroCC CzechiaEuroCC GermanyEuroCC MontenegroEuroCC PolandEuroCC Sweden, and EuroCC Slovenia invite you to the N-Ways to GPU Programming Bootcamp, which will be held online from 8-9 April 2025. The application deadline is 10 March 2025.

The N-Ways to GPU Programming Bootcamp offers a comprehensive introduction to GPU programming. Participants will learn about various methods for adapting scientific applications to GPUs using NVIDIA CUDAOpenACC, OpenMP offloading, and standard programming languages.

Throughout the bootcamp, attendees will work alongside teaching assistants to explore multiple GPU programming models. They will also learn how to analyze GPU-enabled applications using NVIDIA Nsight Systems. The program includes hands-on activities that allow participants to apply their newly acquired skills to real-world problems.

Course details

  • Content level Content level: Basic = (100%) + Intermediate = (0%) + Advanced = (0%)
  • Entry level : Basic – no prior GPU programming knowledge is required
  • Prerequisites : Basic experience with C/C++ or Fortran
  • Target audience : Course for academia, industry, and public administration.
  • Course format : This course will be delivered as a LIVE ONLINE COURSE (using Zoom), All communication will be done through Zoom, Slack, and email.

Registration form and more info : https://events.vsc.ac.at/event/179/

BioExcel Workshop Balkan Edition

2 Days Hands-On Workshop: Hybrid Learning Experience jointly organized by BioExcel and supported by Sofia University “St. Kliment Ohridski”, Faculty of Chemistry and Pharmacy & Faculty of Physics, DISCOVERER Supercomputer and National Competence Centres in Bulgaria, North Macedonia, Romania, Serbia and Montenegro, this hydrid workshop will offer participants the chance to engage both on-site and online. The workshop will focus on the use of BioExcel core codes such as GROMACS, HADDOCK and PMX with a strong emphasis on hands-on practical sessions and guidance from leading experts in the field.

  • When & Where: May 21–22, 2025 | Sofia University, Bulgaria & Online
  • Apply by: April 15, 2025
  • Don’t miss out and boost your research skills! More info and registration : https://bioexcel-balkan-workshop.com/

Scientific Paper on Breast Cancer Detection Using Deep Learning at IT2025

At the IT2025 IEEE conference in Žabljak, researchers from the University of Donja Gorica presented their latest study on the use of artificial intelligence (AI) for breast cancer diagnostics. The research explores the application of deep learning models, ResNet152 and DenseNet121, for analyzing mammographic images. In addition to clinical results, the study highlights the implications of using high-performance computing (HPC) infrastructure to optimize model training and evaluation. By transferring the experimental setup to HPC resources, the research opens pathways for faster development cycles, exploration of more complex architectures, and scalability for real-world implementation.

ABSTRACT – Artificial Intelligence is rapidly advancing the medical field by providing innovative disease diagnosis, treatment, and research approaches. This study explores the application of artificial intelligence in breast cancer diagnostics, focusing on using convolutional neural networks and deep learning to analyze mammographic images. ResNet152 and DenseNet121 models were used to classify malignant changes, achieving AUC scores exceeding 0.9, demonstrating their clinical utility. The research emphasizes how artificial intelligence can enhance screening efficiency, expedite diagnostic processes, and facilitate personalized treatment approaches. Ethical considerations, including patient safety and the transparency of artificial intelligence systems, were also analyzed. The findings underscore the potential of artificial intelligence to transform diagnostic procedures for breast cancer and highlight the importance of further research to integrate these technologies into clinical practice.

HPC/AI for Tuberculosis Detection: Advancing X-Ray Diagnosis with Deep Learning at IT2025

Researchers from the University of Donja Gorica presented a deep learning model for automated tuberculosis detection from chest X-rays at IEEE IT2025 conference. Using a convolutional neural network (CNN), the model classifies images as normal or tuberculosis-positive with an impressive 97.55% accuracy. This breakthrough has the potential to speed up diagnoses, reduce radiologist workload, and improve early detection rates, particularly in low-resource healthcare settings. By leveraging AI for fast and reliable medical imaging analysis, this research highlights the growing role of computer vision in modern healthcare and its ability to enhance efficiency and accuracy in disease detection.

ABSTRACT – This article presents a deep learning model that enables fast and accurate diagnosis of tuberculosis based on chest X-rays. The developed model uses convolutional neural network that enable the automatic classification of chest x-rays into one of two classes: Normal or Tuberculosis with a high degree of accuracy. The model achieved an accuracy of 97.55% on the test data set, indicating its potential to open new perspectives for medical professionals in establishing a tuberculosis diagnosis. This model can significantly speed up the diagnostic process, reducing the workload of medical workers and increasing their productivity in the fight against tuberculosis, one of the most common lung diseases.

Paper on Preserving Cultural Heritage Through Speech Synthesis at IT2025

At the IT2025 IEEE Conference in Žabljak, researchers from the University of Donja Gorica presented a study on voice cloning and text-to-speech (TTS) technology for cultural heritage preservation. Their research compared state-of-the-art AI models, including Realtime Voice Cloning (RVC), Tortoise AI, Bark, and Coqui AI, to evaluate how small, high-quality datasets can produce more accurate and natural-sounding speech than large, unstructured ones. The study highlights the potential of AI in preserving the Montenegrin language and oral traditions, enabling the creation of audiobooks, digital archives, and interactive experiences. This research paves the way for more accessible educational resources and enhanced cultural engagement using AI-driven speech synthesis.

ABSTRACT – This research presents a comparative analysis of modern voice cloning systems, focusing on their ability to generate high-quality speech from limited training data. The paper aims to demonstrate that carefully curated smaller datasets can produce superior results to larger, less structured datasets. The investigation of multiple state-of-the-art models, including Realtime Voice Cloning (RVC), Tortoise AI, Bark, and Coqui AI, establishes optimal data preparation protocols and identifies critical factors in training data quality, with particular emphasis on applications for the Montenegrin language and cultural preservation.

Paper on AI-Driven Breast Cancer Detection with Deep Learning at IT2025

At the IT2025 IEEE Conference in Žabljak, researchers from the University of Donja Gorica presented their latest study on using Artificial Intelligence (AI) for breast cancer diagnostics. The research explores the application of deep learning models, ResNet152 and DenseNet121, to analyze mammographic images. Beyond the clinical results, the study emphasizes the implications of leveraging high-performance computing (HPC) infrastructure to optimize model training and evaluation. By porting the experimental setup to HPC resources, the research opens pathways for faster development cycles, the exploration of more complex architectures, and scalability for real-world implementation. 

ABSTRACT – Artificial Intelligence is rapidly advancing the medical field by providing innovative disease diagnosis, treatment, and research approaches. This study explores the application of artificial intelligence in breast cancer diagnostics, focusing on using convolutional neural networks and deep learning to analyze mammographic images. ResNet152 and DenseNet121 models were used to classify malignant changes, achieving AUC scores exceeding 0.9, demonstrating their clinical utility. The research emphasizes how artificial intelligence can enhance screening efficiency, expedite diagnostic processes, and facilitate personalized treatment approaches. Ethical considerations, including patient safety and the transparency of artificial intelligence systems, were also analyzed. The findings underscore the potential of artificial intelligence to transform diagnostic procedures for breast cancer and highlight the importance of further research to integrate these technologies into clinical practice.

EuroCC4SEE F2F Meeting during IT2025: Strategic Insights on HPC/AI Development in the SEE Region

The EuroCC4SEE consortium, consisting of representatives from NCC Serbia, NCC Montenegro, NCC North Macedonia, NCC Turkey, and NCC Bosnia and Herzegovina, gathered for an F2F meeting during the IT IEEE Conference in Žabljak, Montenegro. The meeting aimed to enhance regional collaboration, coordinate training activities, and maximize the impact of NCC’s regional events to promote HPC/AI technologies and advancements across Southeast Europe.

Click to watch video from IT2025

Each NCC shared updates on ongoing projects, collaborative opportunities, and strategic directions, including: developing SME and Startup Ecosystems; focusing on the digitally mature IT sector, PoC prioritization using EuroHPC and national computing infrastructures, enhancing HPC engagement in academia etc.

EuroCC2 and EuroCC4SEE group photo from Feb 20th

The meeting also explored common activities and future initiatives driving the success of EuroCC4SEE, like organizing an SME training series, based on a cross-border survey on SME training needs; hosting large-scale events at the intersection of academia and industry interests and efforts; developing joint PoCs across diverse sectors using regional expertise and resources, investigating service portfolio management system; mobilizing joint efforts to high-impact EU projects etc.

EuroCC4SEE F2F meeting on 21 Feb

By leveraging strategic conferences, collaborative training programs, and joint project initiatives, EuroCC4SEE continues to empower the SEE region to embrace the future of HPC/AI-driven innovations and growth.

EuroCC4SEE NCC representatives took part in the workshop activities on 20 Ffeb