Topics and scope
The scope of the workshop covers among others quantum simulations, quantum algorithms, ɑnd (classical or quantum) machine learning algorithms with a focus on application in Physics ɑnd Medicine.
List of topics:
machine learning methods in medical applications,
machine learning methods in high-energy physics ɑnd astrophysics,
quantum machine learning,
Generative Adversarial Networks for fast simulations both in medicine ɑnd particle physics,
quantum ɑnd quantum-inspired computing algorithms,
novel methods in medical imaging,
High-Performance Computing (HPC) in physics ɑnd medicine, in particular on heterogeneous platforms such as FPGA ɑnd GPU.
EuroCC tutorial on transfer learning in computer vision
Transfer learning is a machine learning (ML) technique of reusing models with pre-trained knowledge obtained for a general ML task, and applying it to another, more specific ML task, with limited training data or computational resources. This hands-on training will cover the following topics in computer-vision-related problems:
- Introduction to transfer learning in computer vision;
- Image classification with feature extraction - using a downloadable model with pre-trained parameters for a custom classification task;
- Image classification with fine-tuning - update parameters of a pre-trained model to get better results;
- Demonstration of a state-of-the-art transfer learning in image classification: BigTransfer;
- Object detection with a custom dataset based on a pre-trained neural network with the YOLO approach.
Hands-on session for quantum circuits and simulation of noisy algorithms
Quantum algorithms are typically expressed as a quantum logic circuits, where the qubits of a quantum computer are sequentially operated by quantum gates. These gates are quantum mechanical counterparts of classical logic gates such as NOT, XOR etc. that enable more powerful computing by using quantum superposition and entanglement.
This hands-on training covers the following
- introduction to quantum circuits
- how to write quantum circuits with Qiskit, IBM's open-source Python library for quantum algorithms
- how to simulate errors and environmental noise during quantum algorithms
EuroCC technical tutorial on LUMI European Pre-Exascale Supercomputer
LUMI is one of the European pre-exascale HPC systems hosted by the LUMI consortium. The LUMI (Large Unified Modern Infrastructure) consortium countries are Finland, Belgium, the Czech Republic, Denmark, Estonia, Iceland, Norway, Poland, Sweden, and Switzerland.
This tutorial presents a technical overview of the system's hardware configuration and programming-level environment. The aim of the course is to popularise the hardware design of the compute nodes and network and associated programming environment. This introductory material is meant to be a quick start for those who consider access to the LUMI resources and a brief introduction to the software tools available and the capabilities of the hardware.