***Wednesday, 16 December 2020, at 11.00***

*Online seminar*

***Nechaevskiy A.V**.*

*Methods and tools for simulating distributed data storage and

processing systems based on the monitoring results*

(based on the PhD thesis)

Modern data storage and processing systems represent composite

distributed software and hardware complexes built using grid and cloud

technologies. Simulation modeling allows one to detect bottlenecks in

the architecture of data centers, to conduct experiments with changing

the topology and replacing resources to check the proposed system

solutions without directly interfering with the functioning of working

setups and to test algorithms for task management and resource

allocation among user groups. At present, the processes of simulation

and monitoring are considered as independent tasks, not related to each

other. To enhance the accuracy of the results, it is required to use the

statistics accumulated during work using monitoring systems as input

data for simulation. This entails the development of software tools that

combine the processes of simulation and monitoring. The presented

software complex SyMSim for simulating data storage and processing

systems implements the synthesis of modeling and monitoring and allows

one to carry out preliminary studies of different options for organizing

the IT infrastructure, to evaluate the capacities of the existing

architecture in solving data storage and processing tasks and to give

recommendations for its optimization. SyMSim was used to simulate the

computing centers of the BM@N and MPD experiments at the NICA

accelerator complex, MPI calculations and the IHEP computing center in

Beijing.

/More information on the seminar and the link to connect via *Webex* are

available at Indico:/https://indico-hlit.jinr.ru/event/217/

В четверг, 26 ноября, состоится Онлайн семинар:

**Семинар научного отдела вычислительной физики**

Четверг, **26 ноября 2020г., 15.00**

Онлайн семинар

I. Hristov1, R. Hristova1, S. Dimova1, P. Armyanov1, N. Shegunov1,

I. Puzynin2, T. Puzynina2, Z. Sharipov2, Z.Tukhliev2

1.Sofia University, Faculty of Mathematics and Informatics, Bulgaria

2.JINR, Laboratory of Information Technologies, Dubna, Russia

“Parallelizing multiple precision Taylor series method for integrating

the Lorenz system”

A hybrid MPI+OpenMP strategy for parallelizing multiple precision Taylor

series method is proposed, realized and tested. To parallelize the

algorithm, we combine MPI and OpenMP parallel techniques together with

the GMP library (GNU multiple precision library) and the tiny MPIGMP

library. The details of the parallelization are explained on the

paradigmatic model of the Lorenz system. We succeeded to compute a

reliable trajectory for the Lorenz attractor in the rather long time

interval [0, 7000]. The solution was checked by comparing the results

for 2700-th order Taylor series method and precision ~ 3374 decimal

digits with those with 2800-th order and precision ~ 3510 decimal

digits. With 192 CPU cores, the 2800-th order computation lasted ~148

hours with a speedup ~103.

Информация о семинаре и ссылка на подключение размещены в Indico:

https://indico-hlit.jinr.ru/event/211/

=========================

Подключение к семинару:

https://meet.google.com/sqi-nmmu-cjs

**Friday, 23 October 2020, 11.00, Conference-Hall LIT**

Online via Webex

**Sapozhnikov A.A.**

“Magnetic system modelling using method of volume integral equations with

piecewise-linear approximation of the field within ferromagnetic”

(Materials of a PhD thesis)

We consider the application of the volume integral method to the

magnetic system calculations. The major stages of modelling process are

discussed: the discretization of initial equations, the description of

the algorithm for dividing the area into elements, the calculation of

matrix elements for discretization problem and the solution for the

obtained system of non-linear equations. The results of modelling of

magnetic systems using the discussed method are presented and compared

with calculations performed by other programs.

**FLNP SEMINAR**

**October 09, 2020 (Friday), 11-00**

FLNP Conference hall (3rd floor)

https://jinr.webex.com/jinr/j.php?MTID=m47850dc820c62cf16fb69e1ca88fc3e2

The IBR-3 pulsed research reactor – optimization of parameters “Method

of reducing the level of power fluctuations in pulsed reactors”

**Shabalin E.P., Hassan A.A., Rzyanin M.V., Kulikov S.A.**

**Thursday, 1 October 2020, 11.00, Room 310**

Online via Webex

**E.E. Perepelkin abcd , B.I. Sadovnikov b, N.G. Inozemtseva cd,
E.V. Burlakov bd, R.V. Polyakova a**

**a **Joint Institute for Nuclear Research

**b **Lomonosov Moscow State University

**c **Dubna State University

**d **Moscow Technical University of Communications and Informatics

“EFFECTIVE NUMERICAL ALGORITHM FOR CONSTRUCTING THE WIGNER FUNCTION OF A QUANTUM SYSTEM WITH A POLYNOMIAL POTENTIAL IN THE PHASE SPACE”

When considering quantum systems in the phase space, the Wigner

function is used as a function of the quasi-probability density. Finding

the Wigner function is related to the calculation of the Fourier

transform of a certain composition of wave functions of the

corresponding quantum system. As a rule, the knowledge of the Wigner

function is not the ultimate goal, and computations of the average

values of different quantum characteristics of a system are required.

An explicit solution of the Schrödinger equation can be obtained only

for a narrow class of potentials; therefore, numerical methods to find

wave functions are used in most cases. Consequently, finding the Wigner

function is associated with the numerical integration of grid wave

functions. When considering a one-dimensional system, it is obligatory

to calculate N2 Fourier integrals of the grid wave function. To provide

the required accuracy for the wave functions corresponding to the higher

states of a quantum system, a larger number of grid nodes is needed.

The goal of the given work was to construct a numerical-analytical

method for finding the Wigner function, which would significantly reduce

the number of computational operations. Quantum systems with polynomial

potentials, for which the Wigner function is represented as a series in

some known functions, was considered.

The work was supported by the RFBR grant No. 18-29-10014.

https://webmail.jinr.ru/?_task=mail&_action=compose

**Friday, 14 August 2020, at 15.00**

Online seminar via Zoom

**P.B. Kats*, K.V. Halenka*, O.O. Voskresenskaya****

*Brest State A.S. Pushkin University, Belarus

**Joint Institute for Nuclear Research, Dubna, Russia

“Numerical and analytical calculations of the normalized Mott cross

section, as well as of the Mott−Bloch and Lindhard−Sørensen corrections

to the Bethe formula at moderately relativistic energies”

The report presents the results of numerical and analytical calculations

of the normalized Mott scattering cross section using a number of

earlier methods and a method proposed by the authors of this work. It is

demonstrated that applying the given method, along with the method of

Lijian et al., is preferable for relevant calculations. The results of

the numerical calculation of the Lindhard−Sørensen correction and the

total Mott−Bloch correction to the Bethe stopping formula for heavy ion

ionization energy losses, which was obtained by three different methods,

are also presented for the ranges of a gamma factor of approximately 1 ≲

γ ≲ 10 and the ion nuclear charge number 6 ≤ Z ≤ 114. It is shown that

the accurate calculation of the Mott−Bloch corrections based on the

“Mott exact cross section” using a method previously proposed by one of

the authors gives excellent agreement between its values and the values

of the Lindhard−Sørensen corrections in the γ and Z ranges under

consideration. In addition, it is demonstrated that the results of

stopping power calculations obtained by the two above-mentioned rigorous

methods coincide with each other up to the seventh significant digit and

provide the best agreement with experimental data in contrast to the

results of some approximate methods, such as the methods of Ahlen,

Jackson−McCarthy, etc.

Thursday, 2**4 September 2020, 15.00, Conference-Hall LIT**

Online via Webex

Indico: https://indico-hlit.jinr.ru/event/204/

**Sapozhnikov A.A.**

“Magnetic system modelling using method of volume integral equations with

piecewise-linear approximation of the field within ferromagnetic”

(Materials of a PhD thesis)

We consider the application of the volume integral method to the

magnetic system calculations. The major stages of modelling process are

discussed: the discretization of initial equations, the description of

the algorithm for dividing the area into elements, the calculation of

matrix elements for discretization problem and the solution for the

obtained system of non-linear equations. The results of modelling of

magnetic systems using the discussed method are presented and compared

with calculations performed by other programs.

Wednesday, **29 July 2020, 3:00 PM**

Online seminar via Webex

https://indico-hlit.jinr.ru/event/198/

**Igor Pelevanyuk**

“Integration of geographically distributed heterogeneous resources based

on the DIRAC Interware”

The DIRAC Interware platform enables the integration of distributed

heterogeneous computing resources and storage systems into a unified

system. Since 2009, it has been developed as a versatile open-source

tool. DIRAC comprises a set of services related to load and data

management, a web interface, resource consumption accounting,

authorization and authentication, workflow management and some others.

Four interfaces, namely, a web interface, a command line interface, a

Python programming interface and a REST interface, are provided to

users.

At present, the DIRAC-based unified environment, which includes both

computing resources and data storage systems, is used to generate and

reconstruct events of the MPD experiment, to study the SARS-CoV-2 virus

within the Folding@Home project on available cloud resources and to

integrate clouds of the JINR Member States’ organizations into a

distributed platform.

The talk will cover the major aspects of using DIRAC to start jobs and

interact with data.

The information on the workshop and the link to connect via Webex are

available at Indico:

https://indico-hlit.jinr.ru/event/198/

18 June 2020 at 3:00 PM (online format)

“Information system for the tasks of radiation biology

(joint project of LIT and LRB)”

The workshop is dedicated to a joint project of LIT and LRB, which is

focused on the creation of an information system for analyzing

behavioral and pathomorphological changes in the central nervous system

in the study of the effects of ionizing radiation and other factors on

biological objects. The information system is based on computer vision

algorithms within machine and deep learning technologies, modern IT

solutions for data storage, processing and visualization. The

information system will allow one to accelerate and simplify work with

experimental data for different research groups, as well as to elaborate

effective methods of prevention and protection from ionizing radiation.

The information system is being created on the basis of the HybriLIT

heterogeneous platform of JINR.

Workshop program

• I. Kolesnikova (LRB JINR)

Setting tasks for the development of an information system to analyze

morphofunctional changes in the central nervous system when studying the

effects of ionizing radiation and other damaging factors.

• Yu. Severiukhin (LRB JINR)

Noldus Ethnovision XT for the analysis of behavioral responses of small

laboratory animals.

• Yu. Butenko (LIT JINR)

Development of a service for conducting radiobiological studies on the

HybriLIT platform.

• D. Marov (LIT JINR, Dubna State University)

Development of a web service for analyzing functional and morphological

changes in the central nervous system of irradiated animals.

• A. Stadnik (LIT JINR)

Algorithms for image segmentation based on the neural network approach

in the study of morphofunctional changes in the central nervous system.

• A. Bulatov (LIT JINR)

Algorithms of computer vision for the analysis of behavioral responses

of small laboratory animals.

More information on the workshop and the link to connect via Webex are

available at Indico:

https://indico-hlit.jinr.ru/event/196/