scholarly journals Service for parallel applications based on JINR cloud and HybriLIT resources

2019 ◽  
Vol 214 ◽  
pp. 07012 ◽  
Author(s):  
Nikita Balashov ◽  
Maxim Bashashin ◽  
Pavel Goncharov ◽  
Ruslan Kuchumov ◽  
Nikolay Kutovskiy ◽  
...  
Keyword(s):  
High Performance ◽  
Cloud Service ◽  
Parallel Applications ◽  
Cloud Infrastructure ◽  
Modular Architecture ◽  
Practical Applications ◽  
Speed Up ◽  
Scientific Results ◽  
Computational Resources ◽  
Performance Computing

Cloud computing has become a routine tool for scientists in many fields. The JINR cloud infrastructure provides JINR users with computational resources to perform various scientific calculations. In order to speed up achievements of scientific results the JINR cloud service for parallel applications has been developed. It consists of several components and implements a flexible and modular architecture which allows to utilize both more applications and various types of resources as computational backends. An example of using the Cloud&HybriLIT resources in scientific computing is the study of superconducting processes in the stacked long Josephson junctions (LJJ). The LJJ systems have undergone intensive research because of the perspective of practical applications in nano-electronics and quantum computing. In this contribution we generalize the experience in application of the Cloud&HybriLIT resources for high performance computing of physical characteristics in the LJJ system.

scholarly journals Evolution and Perspectives of the Service for Parallel Applications Running at JINR Multifunctional Information and Computing Complex

2020 ◽  
Vol 226 ◽  
pp. 03002
Author(s):  
Nikita Balashov ◽  
Nikolay Kutovskiy ◽  
Daria Priakhina ◽  
Ivan Sokolov
Keyword(s):  
Cloud Service ◽  
Parallel Applications ◽  
Web Interface ◽  
Modular Architecture ◽  
File Storage ◽  
Wide Range ◽  
Multiple Tasks ◽  
Different Types ◽  
Speed Up ◽  
Computational Resources

Nowadays scientists use cloud computing as a routine tool in a lot of fields of their research. Various Multifunctional Information and Computing Complex (MICC) resources are provided for JINR users to perform a wide range of scientific computations. The JINR cloud service for parallel applications was developed in order to simplify scientists’ work on running similar tasks but on different MICC resources and also to speed up the process of reaching significant results. There are several components with a flexible and modular architecture that allow running a various number of applications using different types of computational resources. The service is constantly developing and improving with the help of the users’ feedback. Some changes in web-interface were made to improve users’ experience: there was added the possibility to choose a certain type of particular application, to set a description for a job, to run multiple tasks, to notify a user about successful job submission and its completion. Moreover, accessibility of job results was reworked: when the job is done, its output is uploaded at the external file storage, where it becomes available at the auto-generated unique URL for downloading by the user and further analysis and/or visualization.

Cloud Computing for Scientific Simulation and High Performance Computing

2013 ◽  
pp. 51-70
Author(s):  
Adrian Jackson ◽  
Michèle Weiland
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Parallel Programs ◽  
Small Scale ◽  
Cloud Infrastructure ◽  
Scientific Simulations ◽  
Cloud Infrastructures ◽  
Performance Computing

This chapter describes experiences using Cloud infrastructures for scientific computing, both for serial and parallel computing. Amazon’s High Performance Computing (HPC) Cloud computing resources were compared to traditional HPC resources to quantify performance as well as assessing the complexity and cost of using the Cloud. Furthermore, a shared Cloud infrastructure is compared to standard desktop resources for scientific simulations. Whilst this is only a small scale evaluation these Cloud offerings, it does allow some conclusions to be drawn, particularly that the Cloud can currently not match the parallel performance of dedicated HPC machines for large scale parallel programs but can match the serial performance of standard computing resources for serial and small scale parallel programs. Also, the shared Cloud infrastructure cannot match dedicated computing resources for low level benchmarks, although for an actual scientific code, performance is comparable.

The Sicilian Grid Infrastructure for High Performance Computing

2010 ◽  
Vol 1 (1) ◽  
pp. 40-54 ◽  
Author(s):  
Carmelo Marcello Iacono-Manno ◽  
Marco Fargetta ◽  
Roberto Barbera ◽  
Alberto Falzone ◽  
Giuseppe Andronico ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Parallel Applications ◽  
Grid Infrastructure ◽  
Scheduling Policy ◽  
Computing Paradigm ◽  
Regional Area ◽  
Computer Fluid Dynamics ◽  
Grid Infrastructures ◽  
Performance Computing

The conjugation of High Performance Computing (HPC) and Grid paradigm with applications based on commercial software is one among the major challenges of today e-Infrastructures. Several research communities from either industry or academia need to run high parallel applications based on licensed software over hundreds of CPU cores; a satisfactory fulfillment of such requests is one of the keys for the penetration of this computing paradigm into the industry world and sustainability of Grid infrastructures. This problem has been tackled in the context of the PI2S2 project that created a regional e-Infrastructure in Sicily, the first in Italy over a regional area. Present article will describe the features added in order to integrate an HPC facility into the PI2S2 Grid infrastructure, the adoption of the InifiniBand low-latency net connection, the gLite middleware extended to support MPI/MPI2 jobs, the newly developed license server and the specific scheduling policy adopted. Moreover, it will show the results of some relevant use cases belonging to Computer Fluid-Dynamics (Fluent, OpenFOAM), Chemistry (GAMESS), Astro-Physics (Flash) and Bio-Informatics (ClustalW)).

scholarly journals GITIRBio: A Semantic and Distributed Service Oriented- Architecture for Bioinformatics Pipeline

2015 ◽  
Vol 12 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Luis F. Castillo ◽  
Germán López-Gartner ◽  
Gustavo A. Isaza ◽  
Mariana Sánchez ◽  
Jeferson Arango ◽  
...  
Keyword(s):  
High Performance ◽  
Service Oriented Architecture ◽  
Command Line ◽  
Bioinformatics Pipeline ◽  
Front End ◽  
First Approximation ◽  
Service Oriented ◽  
Computational Resources ◽  
Multiple Sequences ◽  
Performance Computing

Summary The need to process large quantities of data generated from genomic sequencing has resulted in a difficult task for life scientists who are not familiar with the use of command-line operations or developments in high performance computing and parallelization. This knowledge gap, along with unfamiliarity with necessary processes, can hinder the execution of data processing tasks. Furthermore, many of the commonly used bioinformatics tools for the scientific community are presented as isolated, unrelated entities that do not provide an integrated, guided, and assisted interaction with the scheduling facilities of computational resources or distribution, processing and mapping with runtime analysis. This paper presents the first approximation of a Web Services platform-based architecture (GITIRBio) that acts as a distributed front-end system for autonomous and assisted processing of parallel bioinformatics pipelines that has been validated using multiple sequences. Additionally, this platform allows integration with semantic repositories of genes for search annotations. GITIRBio is available at: http://c-head.ucaldas.edu.co:8080/gitirbio

DISSIPATIVE PARTICLE DYNAMICS: INTRODUCTION, METHODOLOGY AND COMPLEX FLUID APPLICATIONS — A REVIEW

2009 ◽  
Vol 01 (04) ◽  
pp. 737-763 ◽  
Author(s):  
E. MOEENDARBARY ◽  
T. Y. NG ◽  
M. ZANGENEH
Keyword(s):  
High Performance ◽  
Dissipative Particle Dynamics ◽  
Coarse Graining ◽  
Particle Dynamics ◽  
Hydrodynamic Behavior ◽  
Computational Speed ◽  
Speed Up ◽  
Complex Fluid ◽  
Performance Computing ◽  
Dpd Simulation

The dissipative particle dynamics (DPD) technique is a relatively new mesoscale technique which was initially developed to simulate hydrodynamic behavior in mesoscopic complex fluids. It is essentially a particle technique in which molecules are clustered into the said particles, and this coarse graining is a very important aspect of the DPD as it allows significant computational speed-up. This increased computational efficiency, coupled with the recent advent of high performance computing, has subsequently enabled researchers to numerically study a host of complex fluid applications at a refined level. In this review, we trace the developments of various important aspects of the DPD methodology since it was first proposed in the in the early 1990's. In addition, we review notable published works which employed DPD simulation for complex fluid applications.

scholarly journals An Architecture for Developing Cyber Environments using Multiple HPC Infrastructures for e-Science Applications

2015 ◽  
Author(s):  
Felipe Maciel ◽  
Carina Oliveira ◽  
Renato Juaçaba Neto ◽  
João Alencar ◽  
Paulo Rego ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Scientific Applications ◽  
Computational Resources ◽  
Performance Computing

In this paper, we propose a novel architecture to allow the implementation of a cyber environment composed of different High Performance Computing (HPC) infrastructures (i.e., clusters, grids and clouds). To access this cyber environment, scientific researchers do not have to become computer experts. In particular, we assume that scientific researchers provide a description of the problem as an input to the cyber environment and then get their results without being responsible for managing the computational resources. We provide a prototype of the architecture and introduce an evaluation which studies a real workload of scientific applications executions. The results show the advantages of the proposed architecture. Besides, we highlight this work provides guidelines for developing cyber environments focused on e-Science.

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