Ruslan Pacevič

Dr. Ruslan Pacevič

Department of Graphical Systems, Vilnius Gediminas Technical University
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2018 in Chemical Engineering Research and Design
Verified
Journal Article
Closed access
RKRimantas Kacianauskas
Rimantas Kacianauskas
VRVytautas Rimša
Vytautas Rimša
AKArnas Kačeniauskas
Arnas Kačeniauskas
AMAlgirdas Maknickas
Algirdas Maknickas
DVDarius Vainorius
Darius Vainorius
RPRuslan Pacevič
Ruslan Pacevič

1 January 2017 in Advances in Engineering Software
Verified
Journal Article
Closed access
AKA. Kačeniauskas
A. Kačeniauskas
RPRuslan Pacevič
Ruslan Pacevič
VSV. Starikovičius
V. Starikovičius
AMAlgirdas Maknickas
Algirdas Maknickas
MSM. Staškūnienė
M. Staškūnienė
GDG. Davidavičius
G. Davidavičius

1 January 2017 in Advances in Engineering Software
Verified
Journal Article
Closed access
RPRuslan Pacevič
Ruslan Pacevič
AKA. Kačeniauskas
A. Kačeniauskas

11 August 2021 in Applied Sciences
Verified
Journal Article
Open access
PDF file
OBOleg Bystrov
Oleg Bystrov
RPRuslan Pacevič
Ruslan Pacevič
AKArnas Kačeniauskas
Arnas Kačeniauskas
The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS.

1 June 2015 in Advances in Engineering Software
Verified
Journal Article
Closed access
RPRuslan Pacevič
Ruslan Pacevič
AKArnas Kačeniauskas
Arnas Kačeniauskas
DMDarius Markauskas
Darius Markauskas

23 July 2023 in Concurrency and Computation: Practice and Experience
Verified
Journal Article
Closed access
OBOleg Bystrov
Oleg Bystrov
RPRuslan Pacevič
Ruslan Pacevič
AKArnas Kačeniauskas
Arnas Kačeniauskas