Welcome and Agenda review

Introduction to EuroCC & the training events

• Nikos Bakas (GRNET)

Parallelism – Essential Concepts for HPC

• Lena Kanellou (FORTH)

Essential elements and fundamental principles of parallelism. Elementary techniques and programming frameworks. What are the main applications and what is the role of GPUs. What they mean for machine learning algorithms.

Building/Engineering high performance streaming solutions: experiences from our research for IoT

• Anastasios Gounaris (AUTH)

Experiences designing and engineering high-performance streaming solutions tailored for the unique challenges of IoT data. Architectural choices, scalability strategies, and lessons learned from prototyping and deploying systems that handle massive, real-time data flows. Open challenges and future directions for building robust, efficient streaming infrastructures that can keep pace with the rapid growth of IoT.

Scalable Simulations: Parallel Strategies for Plasma Science from the Plasma-PEPSC CoE

• Kallia Chronaki (FORTH)

Tutorial: Introduction to Pytorch and the Distributed Data Parallel module (DDP)

• Polidoros Dafnomilis (FORTH)

Basics and main functions of PyTorch, one of the most popular tools for developing machine and deep learning models. Installation and basic use of PyTorch. Introduction into the Distributed Data Parallel library.

Demo - Tutorial: YoloV8

• Klodjan Hidri (FORTH)

Core concepts and practical steps for using YOLOv8 in object detection tasks. Key components of the architecture and how to prepare custom datasets. How to train, fine-tune, and run inference on images and video. What it means for real-world computer vision applications and deployment.

Open Discussion and Q&A