Following major upgrades of the ALICE detector during the second long shutdown, the data-taking capabilities increased by two orders of magnitude. Consequently, the ALICE distributed infrastructure was improved to enable analysis on exceptionally large data samples and to optimise the analysis process. This was carried out by developing new tools for Run 3, O2 and Hyperloop. The O2 analysis...
Mirages (fata morgana) can appear for example above water bodies in our natural environment, when certain atmospheric conditions are satisfied, e.g. the water is warmer than the ambient air, creating a near-surface temperature-gradient resulting in a quick variation of the refractive index of air. The size of the visible mirage carries information on the overall difference in temperature....
Hastlayer (https://github.com/Lombiq/Hastlayer-SDK) is an open-source tool to increase the performance and decrease the power consumption of .NET applications by accelerating them with FPGAs. It converts standard .NET Common Intermediate Language (CIL) bytecode into equivalent VHDL constructs which can be implemented in hardware. The cloud-available Xilinx Alveo family of boards are supported...
Research infrastructures play key role in large-scale and collaboration researches. Each country should have its own network of these. In Hungary recently a list of the top 50 research infrastructures was put together in close connection with the researcher community. How can these help to participate in international collaborations? How can they be best utilised by the researchers? The...
The talk wil highlights some works of the Department of Computational Sciences: new advances in the analysis of interaction of systems, in particular causal discovery. Towards the end a new initiative, the foundation of the Society of Scientific Computing will be announced.
We give a short introduction to a new Hungarian online community dedicated to GPU programming. Our aim is to connect developers and researchers speaking Hungarian to get to know each other and be able to discuss, learn and share expertise in GPU technologies, programming, and related fields, including computer graphics, education, and more.
Recently, employing photonic quantum computers for machine learning purposes has gotten more attention, hence the need for efficient simulation of photonic quantum machine learning is key in this research area. To ease simulation, automatic differentiation of photonic quantum circuits is essential, for which a Piquasso implementation is presented.
Cystic fibrosis (CF) is a hereditary disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein, resulting in the loss of function of this ion channel in the plasma membrane of epithelial cells. CFTR is composed of two transmembrane domains and two intracellular nucleotide-binding domains (NBDs), with the disordered R-domain wedged between them....
We have investigated the synchronization transition of the Shinomoto-Kuramoto model on networks of the fruit-fly and two large human connectomes. This model contains a force term, thus is capable of describing critical behavior in the presence of external excitation. By numerical solution we determined the crackling noise durations with and without thermal noise and showed extended...
In this talk, I will present my experiences building a range of Computational Fluid Dynamics applications on LUMI that use a variety of parallelization approaches, such as HIP, OpenMP offload, and SYCL. Given the relatively new AMD GPU platform, I discuss issues and limitations that affect development, debugging and performance analysis. I show a contrasting analysis of performance as a...
Laser induced fusion with simultaneous volume ignition, a spin-off from relativistic heavy ion collisions, was suggested, where implanted nano antennas regulate the light absorption in the fusion target [1,2]. Recent studies of resilience of the nano antennas in vacuum [3] and UDMA-TEGDMA medium [4] concluded that the lifetime of the plasmonic effect is longer in medium, however, less energy...
Making a given high-voltage power grid more stable and reliable has become a relevant question, especially when considering the current energetic situation or future development plans to augment and interconnect the existing network with renewable energy sources. Understanding the behavior and identifying the critical nodes and links of the network constructed from the power grid data, give us...
The interplay of quantum and classical simulation and the delicate divide between them is in the focus of massively parallelized tensor network state (TNS) algorithms designed for high performance computing (HPC). In this contribution, we present novel algorithmic solutions together with implementation details to extend current limits of TNS algorithms on HPC infrastructure building on...
Following up on the similarly named talk in 2021, the evolution of standards in HPC haven't slowed down a bit. If anything, research and adoption have accelerated. There is a fair amount to be excited over around Khronos standards and open technologies.
While the compilation of quantum algorithms is an inevitable step towards executing programs on quantum processors, the decomposition of the programs into elementary quantum operations poses serious challenge, mostly because in the NISQ era it is advantageous to compress the executed programs as much as possible.
In our recent work [1] we proposed the utilization of FPGA based data-flow...
We present an improved efficiency Leading Zero Counter for Xilinx FPGAs which improves the path delay while maintaining the resource usage, along with generalizing the scheme to variants whose inputs are of any size. We also show how the Ultrascale architecture also allows for better Intellectual Property solutions of certain forms of this circuit with its newly introduced logic elements. We...
Quadratic unconstrained binary optimization (QUBO) problems, including MAX-CUT as a special case, are important hard problems of mathematical optimization. Recently they have attracted much attention because they are the very problems that quantum annealers can address directly: QUBO problems are equivalent to the Ising model, a central and extensively studied problems in physics.
Even...
Closed quantum systems are described by a deterministic, linear evolution of their quantum states. Observation of a system breaks this rule: we gain information and the description becomes probabilistic. Provided we have multiple copies of a system in the same quantum state, we can design a protocol consisting of a joint unitary operation on all of them and a subsequent measurement on all but...
The GigaBit Transceiver (GBT) and the low power GBT (lpGBT) link architecture and protocol have been developed by CERN for physical experiments in the Large Hadron Collider as a radiation-hard optical link between the detectors and the data processing FPGAs (https://gitlab.cern.ch/gbt-fpga/). This presentation shows the details of how to implement a large array of GBT/lpGBT links (up to 48 x...
The recent rapid development in the generative methods of artificial intelligence makes it more and more urgent to understand, what is the intelligence they manifest, what are the limits and where are the breakthrough points for a next generation AI. In the talk we examine, what is the relation of the present-day leading AI applications to human thinking, in particular the "fast" and "slow"...
Some applications of Monte Carlo simulation require the generation of a
large number of small grids of bits (e.g. tiles or boards of 32 by 32 bits) with a
given number of bits set to one, the rest is set to zero. Conventional sequential
algorithms generate them by randomly selecting empty sites until the given
number of set sites is reached, which is not an efficient solution. In this...
In this talk, we will describe our experience with the GPULab cluster in accelerating EEG signal processing and data analysis. GPULab is a large GPU computing resource of IMEC (Belgium) accessible for researchers through the SLICES-SC research infrastructure project. The system consists of a set of heterogeneous clusters, each with their own characteristics (GPU model, CPU speed, memory, bus...
The Artificial Intelligence National Laboratory Hungary (MILAB) is a research consortium of 11 institutions in Hungary. MILAB researchers use GPUs to accelerate the training of deep neural networks for machine vision tasks in object detection, surveillance and medical imaging applications. We train and evaluate deep neural networks for natural language processing tasks, such as sentiment...
Proton therapy is an emerging method against cancer. One of the main developments is to increase the accuracy of the Bragg-peak position calculation, which requires more precise relative stopping power (RSP) measurements. An excellent choice is the application of proton computed tomography (pCT) systems which take the images under similar conditions to treatment as they use the same...
Proton therapy is a promising method for cancer treatment, where the energy deposit may be focused on the cacerous cells, hence providing a much faster method with less side effects as a traditional radiation therapy. However, a good diagnostic tool, a "CT" with ptotons is missing to reach the desired accuracy. Here, we model a new tool chain, where we generate events, detected by the planned...
The application of deep learning in gigapixel whole slide image analysis has shown promising results in terms of accuracy and efficiency compared to traditional image analysis techniques. Transformer based models as the current state-of-the-art algorithms are capable of identifying and classifying various structures and patterns within the tissue, providing insights into the underlying...
In HPC, a common method is decomposing large equation systems into a batched
problem of small equation systems. Such small systems are
Tridiagonal/pentadiagonal matrix systems frequently arise in
finite-difference methods for solving multi-dimensional PDEs in various
applications. Such systems are, for instance, present in computational fluid
dynamics (CFD) for flow solvers based on...
PyTorch is a production-ready framework for machine learning in
Python, offering a robust ecosystem and a large community behind. It
takes advantage of GPUs, HPC, and cloud environments. While primarily
aimed for machine learning applications, it includes tools for a broad
area of numerical applications, including, e.g. linear algebra,
tensors, random numbers, statistics, optimization,...
The searching for ephemeral liquid water on Mars is an ongoing activity. After the recession of the seasonal polar ice cap on Mars, small water ice patches may be left behind in shady places due to the low thermal conductivity of the Martian surface and atmosphere. During the southern summer, these patches may be exposed to direct sunlight and warm up rapidly enough for the liquid phase to...
We give a sort introduction of a new Hungarian online community
dedicated to GPU programming. Our aim is to connect developers and
researchers speaking hungarian to get to know each other, and be able
to discuss, learn and share expertise in GPU technologies, programming
and related fields, including computer graphics, education and more.
