GPU Day 2022

Session

Session IV

20 Jun 2022, 16:00

Hotel Mercure Budapest Castle Hill

32. Machine learning methods for Schlieren imaging of a plasma channel in tenuous atomic vapor

Mr Mihály András Pocsai (Wigner RCP)

20/06/2022, 16:00

Lecture

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...

35. Strategies for multi-GPU PIC/MCC plasma simulation implementation on pre-exascale supercomputers

Zoltan Juhasz (University of Pannonia)

20/06/2022, 16:20

Lecture

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...

51. Preliminary results of the tuned HIJING++ heavy-ion event generator

Balazs Majoros (Wigner FK)

20/06/2022, 16:40

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...

46. The highly increased number of protein structures calls for high performance algorithms

Tamas Hegedus (Semmelweis University)

20/06/2022, 17:00

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...