Project reference: 2119 The paradigm of quantum computers is completely different from the paradigm of classical digital computers. Understanding this paradigm will allow the student to understand, for example, how it is possible that quantum computers are able to solve …
Project reference: 2118 Quantum computing is one of the scientific hot-topics nowadays with the potential to vastly improve our computation capacity in certain areas due to its use of quantum-bits offering superpositions and much faster computation, subsequently. Thus, it seems …
Project reference: 2121 Today’s supercomputing hardware provides a tremendous amount of floating point operations (FLOPs). However, most FLOPs can only be harvested easily, if the algorithm does exhibit lots of parallelism. Additionally, efficient use of resources strongly depends on the …
Project reference: 2120 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 …
Project reference: 2115 Python is widely used in scientific research for tasks such as data processing, analysis and visualisation. However, it is not yet widely used for large-scale modelling and simulation on high performance computers due to its poor performance …
Performance of Parallel Python Programs on ARCHER2 Read More »
Project reference: 2114 Recent technological advances allow us to assess millions of genetic data points (>30 million) to identify their involvement in disease. This is a two orders of magnitude increase compared to the data available a few years ago. …
Re-engineering and optimizing Software for the discovery of gene sets related to disease Read More »
Project reference: 2113 Exploitation of renewable energy sources is critical for humanity to timely address issues raised by climate change and for transitioning towards a sustainable zero-carbon economy. MPAS Atmosphere model, developed by the US National Center for Atmospheric Research, …
Investigating Scalability and Performance of MPAS Atmosphere Model Read More »
Project reference: 2112 Datacentre in production are characterized by the combination of extreme parallelism and performance demand. This translates in large number of resources to be management constantly stressed by intense computational patterns. Each of the HW and SW resources …
Combining Big-data, AI and 3D visualization for datacentre optimization Read More »
Project reference: 2111 Automatic techniques for recognition of submarine structures (e.g. canyons) are an absolute novelty in the Oceanographic field. Excluding some preliminary experiments (Ismail et al -2015, Huvenne -2002), right now the recognition on the seabed of structures like …
Project reference: 2110 High Energy Physics (HEP) community traditionally employed High Throughput Computing (HTC) type of facilities for the purpose of LHC data processing and various types of physics analyses. Furthermore, with recent convergence of AI and HPC, it becomes …
Project reference: 2109 High Energy Physics (HEP) community has a large number of various workloads (e.g. pure statistical analysis vs LHC event reconstruction) that differ not only by their requirements (compute vs I/O driven) but also by the capability of …
Project reference: 2108 Solution of independent-particle model (DFT or Hartree-Fock method) is one of the key targets of many quantum chemistry codes. Hartree-Fock method is iterative procedure which consist of two time-consuming steps. First, construction of Fock matrix from integrals …
Efficient Fock matrix construction in localized Hartree-Fock method Read More »
Project reference: 2107 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 …
Project reference: 2106 The NMMB/MONARCH (formerly NMMB/BSC-Dust) (Pérez et al., 2011; Haustein et al., 2012) is an online multi-scale atmospheric dust model designed and developed at the Barcelona Supercomputing Center (BSC-CNS) in collaboration with the NOAA’s National Centers for Environmental …
Project reference: 2105 Biomedical and Life Sciences are two of the main areas presenting a considerable growth in literature through the last decade, which is demonstrated by the increase in articles indexed in PubMed (a database of biomedical articles). An …
Cross-Lingual Transfer learning for biomedical texts Read More »
Project reference: 2104 Machine learning applications will dominate edge and mobile applications in the future. While most of the training takes place on HPC clusters and many are deployed in the cloud, some of these applications still have to run …
Building Resilient Machine Learning Applications (From HPC to Edge) Read More »
Project reference: 2103 High Performance Computing (HPC) clusters have evolved to complex systems with a tremendous number of components. An HPC cluster is much more than the mere sum of its parts. A fast CPU is nothing without a fast …
Precision based differential checkpointing for HPC applications Read More »
Project reference: 2102 Mitigating climate change is one of the most important humankind challenges at the time. Since the 19th century, fossil fuels’ global use has increased and dominated world energy consumption and supply. The rapid rise of global energy …
Computational atomic-scale modelling of materials for fusion reactors Read More »
Project reference: 2101 Outstanding capabilities for computation are useless if data is not where it is needed in time. This is common knowledge in computer architecture, even more so now that systems are extremely parallel and memory bandwidth gets scarcer …
Analysis of data management policies in HPC architectures Read More »
Applications are open from 15th of January 2021 to 12th of April 2021. See the Timeline for more details. PRACE Summer of HPC programme is announcing projects for 2021 for preview and comments by students. Please send questions to coordinators directly by …
