Hastlayer (https://hastlayer.com/) by Lombiq Technologies is a .NET software developer-focused, easy-to-use high-level synthesis tool with the aim of accelerating massively parallel applications. It converts standard .NET Common Intermediate Language (CIL) bytecode into equivalent Very High Speed Integrated Circuit Hardware Description Language (VHDL) constructs which can be implemented in...
OpenCL has gained a name for being one of the most portable programming models for heterogenous programming. It’s 3.0 release improves upon deployment flexibility and most major vendors already ship 3.0 compliant runtimes. Stream HPC is at the forefront of reinvigorating the ecosystem, demonstrating how to make the best use of 3.0 and the latest features. The OpenCL SDK is a 1st party Khronos...
Komondor, the newest 5 petaflops GPU supercomputer of Hungary is on its way to both academic and industrial users. The system includes 200 A100 GPU. The talk will focus on the details of the hardware and software stack, and ways to access and use the system, including the option to run containerized jobs by using web interfaces only.
The HPC Competence Center will offer training on how to use...
Empirical Mode Decomposition (EMD) is an effective tool for the analysis of non-linear and non-stationary signals, which has been widely used in various application fields for noise reduction, feature extraction and classification. Due to its adaptive and data-driven nature, it has been introduced to electroencephalography (EEG) analysis to extract more accurate information in time-frequency,...
Previous simulation studies on human connectomes [1] suggested, that critical dynamics emerge subcrititcally in the so called Griffiths Phases. This is the consequence of the strong heterogeneity of the graphs. Now we investigate this on the largest available brain network, the $21.662$ node fruit-fly connectome, using the Kuramoto synchronizationmodel. As this graph is less heterogeneous,...
The ALICE experiment has undergone a major upgrade for LHC Run 3 and will record 50 times more heavy ion collisions than before.
The new computing scheme for Run 3 replaces the traditionally separate online and offline frameworks by a unified one.
Processing will happen in two phases.
During data taking, a synchronous processing phase performs data compression, calibration, and quality...
Using the kinematic information of the final state particles produced in heavy-ion collisions at relativistic energies, one tries to probe the properties of the very hot and dense medium formed just after the collision. There have been different probes to study the physics associated with such a medium, and one of them is the elliptic flow ($v_2$). In this study, we have employed a deep neural...
Modern proton Computed Tomography (pCT) images are usually reconstructed by algebraic reconstruction techniques (ART). The Kaczmarz-method and its variations are among the most widely used methods, which are iterative solution techniques for linear problems with sparse matrices. It is an interesting question whether statistically-motivated iterations, which have been successfully used for...
In Artificial Intelligence (AI) the success of learning depends crucially on the way we represent the input data. In the talk we overview the criteria of an ideal representation, and associate an entropy formula to them. We also show how these representations work in case of mechanical motion reconstruction from data.
Inventing and fine-tuning laser and plasma based electron accelerators is a hot topic of contemporary physics, either considering experimental, theoretical or applied physics. One of the most prominent experiments in this field is the CERN-AWAKE experiment [1]. In this experiment, electrons are accelerated by the wakefields generated by a series of proton microbunches in a 10-meter-long...
In this talk we describe, compare and evaluate various implementation strategies that can be used to implement massively parallel Particle-in-Cell / Monte Carlo collision low-pressure plasma simulations. Building on our earlier single-GPU 1D and 2D plasma implementations that demonstrated two orders of magnitude speedup, our goal is now to utilise the thousands of GPUs found in pre-exascale...
Monte Carlo event generators became one of the most important tools of modern high-energy physics. They are widely used in the high-energy community to simulate particle collisions, make predictions, and to design experiments.
The HIJING++ (Heavy Ion Jet INteraction Generator) is the successor of the 30 year old Fortran HIJING, completely rewritten in C++, providing multi-thread processing...
The number of unique transmembrane (TM) protein structures doubled in the last four years that can be attributed to the revolution of cryo-electron microscopy. In addition, the AlphaFold2 (AF2) deep learning algorithm also provided a large number of predicted structures with high quality. However, if a specific protein family is the subject of a study, collecting the structures of the family...
In this talk, we introduce Piquasso, a full-stack open source platform for Photonic Quantum Computing built using Python and C++. Piquasso enables users to perform efficient Quantum Computing using continuous variables, which could be used for designing photonic circuits for simulation and machine learning purposes.
Computing the permanent of a matrix finds an important application in the context of boson sampling. Using the BB/FG permanent formula with a reflected binary Gray code, we implemented an FPGA design aimed at maximizing the use of logic and DSP resources to increase the parallelism and reducing the time complexity from $\mathcal{O}(n.2^{n-1})$ to $\mathcal{O}(n.2^{n-3})$. This can be...
In this work, we report on a novel quantum gate approximation algorithm based on the application of parametric two-qubit gates in the synthesis process. The utilization of these parametric two-qubit gates in the circuit design allows us to transform the discrete combinatorial problem of circuit synthesis into an optimization problem over continuous variables. The circuit is then compressed by...
Hadronization is a non-perturbative process, which theoretical description can not be deduced from first principles. Modeling hadron formation, requires several assumptions and various phenomenological approaches. Utilizing state-of-the-art Computer Vision and Deep Learning algorithms, it is eventually possible to train neural networks to learn non-linear and non-perturbative features of the...
We study the inverse problem of reconstructing spectral functions from Euclidean correlation functions via machine learning. We propose a novel neural network, SVAE, which is based on the variational autoencoder (VAE) and can be naturally applied to the inverse problem. The prominent feature of the SVAE is that a Shannon-Jaynes entropy term having the ground truth values of spectral functions...
When light travels through a medium with a changing refractive index, it gets bent towards its higher values. This can produce upside down "mirror" images of a scenery in deserts, over heated roads or above bodies of water. We built a model for the temperature profile based on measurement data, from which we calculated the refractive index of air using another model. We implemented a computer...
The field of mechatronics engineering integrates mechanical systems and control; therefore, the main challenges of both subfields appear simultaneously. A typical task in mechatronics is position control, where the main goal is to reach the desired position or track a predefined trajectory. The primary design task is to determine the stability domain of the control parameters where the...
Targeting ultimate fidelity reactor physics calculations the Dynamic Monte Carlo (DMC) method simulates reactor transients without resorting to static or quasistatic approximations. Due to the capability to harness the computing power of Graphics Processing Units, the GUARDYAN (GpU Assisted Reactor DYnamic ANalysis) code has been recently upscaled to perform pin-by-pin simulations of power...
The outer realm of the Solar System, known either as the trans-Neptunian space or the Kuiper belt, is of great interest among celestial mechanical studies. Its dynamical structure is shaped to a large extent by the mean-motion resonances (MMRs) occurring between the trans-Neptunian objects (TNOs) and (mainly) the Neptune.
In a recent research, we carried out a large-scale survey of the TNOs,...
As the design and mass manufacturing of efficient quantum computers are still subject of intense research, the numerical simulations of quantum systems still rely on classical computation. In this case however the complexity and resource requirements of such algorithms scale exponentially relative to the system size, thus making bigger simulations problematic or even impossible to run.
Our...
Dynamical simulation of the cascade failures on the EU and USA high-voltage power grids has been done via solving the second-order Kuramoto equation. We show that synchronization transition happens by increasing the global coupling parameter $K$ with metastable states depending on the initial conditions so that hysteresis loops occur. We provide analytic results for the time dependence of...
The objective of sonochemistry is to increase the yield of chemical processes in a fluid with ultrasound excitation. It is based on a special case of cavitation called acoustic cavitation. Because of the ultrasound excitation, several bubbles and bubble-clouds can be formed in a liquid. During the radial oscillation of the bubbles, their compression can be so large that the internal...
