Project reference: 2222 Pharmaceutical intervention is always a compromise between unwanted side effects and anticipated interference with a pathological condition. A particular class of well tolerated drugs is formed by small peptides because their building blocks are simply the 20 …
HPC-Derived Affinity Enhancement of Antiviral Drugs Read More »
Project reference: 2220 XDEM is a multi-physics framework for the simulation of granular material (Discrete Element Method) coupled with a fluid (Computational Fluid Dynamics) and running on High Performance Computing platforms. The XDEM software is in continuous development and requires …
Performance Comparison and Regression for XDEM Multi-Physics Application Read More »
Project reference: 2221 In recent years there has been a massive development in the high-performance computing architecture. More precisely, almost all the supercomputers are having the accelerators such as GPUs. On the other hand, there is a big question rising …
Project reference: 2219 CFD is solving time-dependent partial differential equations (PDE), and PDE is solved by numerical approximation, which brings the system of equations (matrices and vectors) that need to be solved either by direct or indirect solvers. These solvers …
Project reference: 2218 The main objective of this SoHPC project is to test how our existing code for energy consumption prediction scales from a local server to supercomputer. We have developed Python and R scripts to retrieve data, store it …
Parallel big data analysis within R for better electricity consumption prediction Read More »
Project reference: 2217 We propose to analize operational logs with machine learning methods. Starting from our previous work where we characterised the operational logs of our cluster computer LISA [1], we propose a continuation that would bring in scope additional …
Project reference: 2216 A reasonable part of the data analytics and statistical modelling community relies on some form of probabilistic programming language and software to implement particular solvers for models written in this language. This approach allows users to specify …
Scaling HMC on large multi-CPU and/or multi-GPGPUs architectures Read More »
Project reference: 2215 Today’s supercomputing hardware provides a tremendous amount of floating point operations (FLOPs). Hierarchical algorithms like the Fast Multipole Method (FMM) can achieve a very good utilization of the FLOPs coming from a single node. However, modern supercomputer …
Chitchat, Gossip & Chatter,- How to efficiently deal with communication Read More »
Project reference: 2214 Simulations of classical or quantum field theories often rely on a lattice discretized version of the underlying theory. For example, simulations of Lattice Quantum Chromodynamics (QCD, the theory of quarks and gluons) are used to study properties of …
Project reference: 2213 As the costs of electricity in Europe are rapidly growing, peaking more than 600 EUR per MWh in the end of 2021 and having a 200 EUR per MWh on regular basis, a stable and reliable as …
Project reference: 2212 Quantum computers are based on a completely different principle than classical computers. The aim of this project is to explain this difference. Thanks to this insight, potential students should then understand, for example, why quantum computers are …
Fundamentals of quantum algorithms and their implementation Read More »
Project reference: 2211 Space is a harsh environment; however, it is not totally void. In the solar system, space is filled with charged particles continuously expelled from the Sun corona. This flow is the so-called “solar wind”. Our goal is …
Project reference: 2210 Direct numerical simulations of turbulence flows are still challenging and need the performance of the fastest super-computers in the world. As the latter are nowadays of heterogeneous architecture, i.e. mixing CPUs and accelerators such as GPUs, algorithms updated. In this …
Project reference: 2209 The numerical simulation of wave propagation phenomena is of great interest in many areas of science and engineering, including seismic and acoustic applications. In this context, the use of time-domain solvers enables to significantly reduce the memory …
Project reference: 2208 Neural networks have shown remarkable performance in lots of domains to solve problems of high complexity. They can, in principle, be used to learn any type of model as they are universal approximators. Their use would be …
Optimization of neural networks to predict results of mechanical models Read More »
Project reference: 2207 Permafrost modeling is important for climate change impacts assessment both in cold areas (especially intensive warming occurring there) and globally (massive quantities of frozen organic C stored in the near surface permafrost). It has also numerous applications …
Project reference: 2206 The Julia language is one of the most modern and effective languages for performing high-performance numerical simulations, particularly in fluid mechanics. This project involves implementing a 2D Julia code simulating the transport of a scalar function with …
Designing a Julia Parallel code for adaptive numerical simulation of a transport problem Read More »
Project reference: 2205 Jobs are the essence of the supercomputing. Users creates jobs to solve their scientific and societal challenges, the supercomputing machine executes the job to obtain the aimed results. Crafting efficient jobs which maximises the performance (or minimise …
A dashboard for on-line assessment of jobs execution efficiency Read More »
Project reference: 2204 The aim of the project is to start the development of methodologies to analyse COPERNICUS satellite data to extract low-resolution bathymetric data in shallow coastal areas where multibeam echosounder data is lacking. These satellite bathymetric extrapolations will …
Automated Extraction of Satellite BAthymetric data by Artificial Intelligence strategies Read More »
Project reference: 2203 Neural networks (NN) and deep learning are two success stories in modern artificial intelligence. They have led to major advances in image recognition, automatic text generation, and even in self-driving cars. NNs are designed to model the …
Neural networks in chemistry – search for potential drugs for COVID-19 Read More »
