scholarly journals Scientific services consolidation methods

2020 ◽  
Vol 22 (4) ◽  
pp. 302-307
Author(s):  
A. A. Zatsarinny ◽  
V. A. Kondrashev ◽  
A. A. Sorokin ◽  
S. A. Denisov
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Service Oriented Architecture ◽  
Materials Science ◽  
Hierarchical Modeling ◽  
Parallel Execution ◽  
Third Party ◽  
Enterprise Service Bus ◽  
Computing Systems ◽  
Stage Of Development

The article discusses methods of consolidating scientific services of a digital platform for integrating a set of scientific services for various fields of science for conducting interdisciplinary research. Solutions for creating consolidated services can be widely used for multilevel, multiscale modeling in the field of materials science, which provides complex modeling at several levels of the hierarchy. Currently, this problem is being solved by creating multicomponent hierarchical software systems on corporate computing systems. With the advent of high-performance cloud computing platforms, it will be possible to order services for solving particular modeling problems as a scientific service. In this case, the tasks of complex hierarchical modeling will be solved by a consolidated service - a service providing sequential-parallel execution of complex modeling components in the form of specialized scientific services. The description of the processes for the provision of scientific services is based on the research methodology and is a research plan (the work process mapping), which describes a set of operations related to time and includes a list of necessary resources for their implementation. In modern conditions of the development of a microservice approach to the creation of computing systems and the evolution of the Service Oriented Architecture and of the Enterprise Service Bus integration, special attention is paid to the problems of efficient integration of platform services. The paper proposes to supplement the existing description of a scientific service with the possibility of ordering a third-party service based on agile integration. This approach will allow at the present stage of development of service architectures to overcome the shortcomings of centralized systems such as Enterprise Service Bus and take advantage of the elasticity of cloud computing and a microservice approach to creating information and computing systems.

scholarly journals The architectures analyzing for computational workflows designing in a distributed environment

2020 ◽  
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Business Processes ◽  
Service Oriented Architecture ◽  
Distributed Environment ◽  
End User ◽  
Distributed Resources ◽  
Computing Architecture ◽  
Performance Computing

The paper presents a model of computational workflows based on end-user understanding and provides an overview of various computational architectures, such as computing cluster, Grid, Cloud Computing, and SOA, for building workflows in a distributed environment. A comparative analysis of the capabilities of the architectures for the implementation of computational workflows have been shown that the workflows should be implemented based on SOA, since it meets all the requirements for the basic infrastructure and provides a high degree of compute nodes distribution, as well as their migration and integration with other systems in a heterogeneous environment. The Cloud Computing architecture using may be efficient when building a basic information infrastructure for the organization of distributed high-performance computing, since it supports the general and coordinated usage of dynamically allocated distributed resources, allows in geographically dispersed data centers to create and virtualize high-performance computing systems that are able to independently support the necessary QoS level and, if necessary, to use the Software as a Service (SaaS) model for end-users. The advantages of the Cloud Computing architecture do not allow the end user to realize business processes design automatically, designing them "on the fly". At the same time, there is the obvious need to create semantically oriented computing workflows based on a service-oriented architecture using a microservices approach, ontologies and metadata structures, which will allow to create workflows “on the fly” in accordance with the current request requirements.

Energy Management in Cloud Computing

2016 ◽  
pp. 293-309 ◽  
Author(s):  
Ganesh Neelakanta Iyer ◽  
Pattabhi Mary Jyosthna ◽  
Suman Jonnalagadda
Keyword(s):  
Cloud Computing ◽  
Co2 Emission ◽  
Business Performance ◽  
High Performance ◽  
Service Providers ◽  
Cloud Service ◽  
High Energy ◽  
Operational Cost ◽  
Computing Systems

Due to the growing demand of businesses, enterprises are concentrating on performance improvement as well as investment reduction for their applications. Cloud Computing, an emerging technology which provides enormous services through internet is the best choice for the enterprises to improve their business performance and to reduce their capital budget. Cloud datacenters have thousands of servers to provide uninterrupted services to the consumers. These High Performance Computing systems consumes high energy, which leads to increase in Cloud Service Providers operational cost. Apart from the operational cost it also increases CO2 emission, which causes Global warming. So many researchers are evolving engineering techniques that are required to improve performance as well as optimization in power consumption. This chapter describes some of the techniques that are used to reduce operational cost, CO2 emission, SLA violation and able to maintain Quality of Service (QoS). It also describes about limitations on existing methods and further enhancement issues for better performance.

A Comprehensive Study on Commercial Applications of Cloud Computing

2020 ◽  
Vol 17 (9) ◽  
pp. 4411-4418
Author(s):  
S. Jagannatha ◽  
B. N. Tulasimala
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
High Performance ◽  
Large Scale ◽  
Service Providers ◽  
Cost Effective ◽  
Computer Hardware ◽  
Computing Technology ◽  
Computing Systems ◽  
Computational Performance

In the world of information communication technology (ICT) the term Cloud Computing has been the buzz word. Cloud computing is changing its definition the way technocrats are using it according to the environment. Cloud computing as a definition remains very contentious. Definition is stated liable to a particular application with no unanimous definition, making it altogether elusive. In spite of this, it is this technology which is revolutionizing the traditional usage of computer hardware, software, data storage media, processing mechanism with more of benefits to the stake holders. In the past, the use of autonomous computers and the nodes that were interconnected forming the computer networks with shared software resources had minimized the cost on hardware and also on the software to certain extent. Thus evolutionary changes in computing technology over a few decades has brought in the platform and environment changes in machine architecture, operating system, network connectivity and application workload. This has made the commercial use of technology more predominant. Instead of centralized systems, parallel and distributed systems will be more preferred to solve computational problems in the business domain. These hardware are ideal to solve large-scale problems over internet. This computing model is data-intensive and networkcentric. Most of the organizations with ICT used to feel storing of huge data, maintaining, processing of the same and communication through internet for automating the entire process a challenge. In this paper we explore the growth of CC technology over several years. How high performance computing systems and high throughput computing systems enhance computational performance and also how cloud computing technology according to various experts, scientific community and also the service providers is going to be more cost effective through different dimensions of business aspects.

scholarly journals THE FEASIBILITY STUDY OF RUNNING HPC WORKLOADS ON COMPUTATIONAL CLOUDS

2017 ◽  
Vol 10 (13) ◽  
pp. 445
Author(s):  
Purvi Pathak ◽  
Kumar R
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
High Performance ◽  
Cloud Environment ◽  
Computing Environment ◽  
Private Cloud ◽  
Computing Systems ◽  
Cloud Computing Environment ◽  
Pros And Cons ◽  
Performance Computing

High-performance computing (HPC) applications require high-end computing systems, but not all scientists have access to such powerful systems. Cloud computing provides an opportunity to run these applications on the cloud without the requirement of investing in high-end parallel computing systems. We can analyze the performance of the HPC applications on private as well as public clouds. The performance of the workload on the cloud can be calculated using different benchmarking tools such as NAS parallel benchmarking and Rally. The workloads of HPC applications require use of many parallel computing systems to be run on a physical setup, but this facility is available on cloud computing environment without the need of investing in physical machines. We aim to analyze the ability of the cloud to perform well when running HPC workloads. We shall get the detailed performance of the cloud when running these applications on a private cloud and find the pros and cons of running HPC workloads on cloud environment.

scholarly journals Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

2021 ◽  
Vol 11 (10) ◽  
pp. 4350
Author(s):  
Huriviades Calderón-Gómez ◽  
Luis Mendoza-Pittí ◽  
Miguel Vargas-Lombardo ◽  
José Manuel Gómez-Pulido ◽  
Diego Rodríguez-Puyol ◽  
...  
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Service Oriented Architecture ◽  
Clinical History ◽  
Computer Assisted ◽  
Care Services ◽  
Architectural Patterns ◽  
Service Oriented ◽  
Microservice Architecture

This article proposes a new framework for a Cloud-based eHealth platform concept focused on Cloud computing environments, since current and emerging approaches using digital clinical history increasingly demonstrate their potential in maintaining the quality of the benefits in medical care services, especially in computer-assisted clinical diagnosis within the field of infectious diseases and due to the worsening of chronic pathologies. Our objective is to evaluate and contrast the performance of the architectural patterns most commonly used for developing eHealth applications (i.e., service-oriented architecture (SOA) and microservices architecture (MSA)), using as reference the quantitative values obtained from the various performance tests and their ability to adapt to the required software attribute (i.e., versatile high-performance). Therefore, it was necessary to modify our platform to fit two architectural variants. As a follow-up to this activity, corresponding tests were performed that showed that the MSA variant functions better in terms of performance and response time compared to the SOA variant; however, it consumed significantly more bandwidth than SOA, and scalability in SOA is generally not possible or requires significant effort to be achieved. We conclude that the implementation of SOA and MSA depends on the nature and needs of organizations (e.g., performance or interoperability).

scholarly journals The main scientific and technical problems of using hybrid HPC clusters in materials science

2020 ◽  
Vol 22 (4) ◽  
pp. 262-267
Author(s):  
K. I. Volovich ◽  
S. A. Denisov
Keyword(s):  
High Performance ◽  
Materials Science ◽  
Parallel Execution ◽  
Cloud Services ◽  
Atomic Scale ◽  
Software Systems ◽  
Technical Problems ◽  
Digital Platforms ◽  
Central Processing ◽  
Materials Modeling

The article discusses the use of hybrid HPC clusters for the execution of software designed to calculate the electronic structure and atomic scale materials modeling. Modern software systems, which are designed to solve the problems of materials science, use the capabilities of various hardware computing accelerators to increase productivity. The use of such computing technologies requires the adaptation of application program code to hybrid computing architectures, which include classic central processing units (CPUs) and specialized graphics accelerators (GPUs).The use of large computing hybrid systems requires the development of methods for ensuring the workloading of such computing systems that will allow efficient use of computing resources and avoid equipment downtime.First of all, these methods should allow parallel execution of user applications using computational accelerators. However, in practice, software environments designed to solve application problems cannot be deployed in the same computing environment due to software incompatibility. In order to overcome this limitation and ensure the parallel execution of diverse types of materials science tasks, the creation of individual task execution environments based on virtualization technologies and cloud technologies.The continuation of virtualization technologies and the provision of cloud services is the construction of digital platforms. The article proposes the use of a digital platform for hosting scientific materials science services that provide calculations using various application software systems. Digital platforms make it possible to provide a unified user interface to scientific materials science services. The platform provides opportunities for finding the necessary scientific services, transferring source data and results between users, the platform and hybrid high-performance clusters.

scholarly journals Advanced IT Outsourcing By Using Cloud Computing Model

2012 ◽  
Vol 2 (2) ◽  
pp. 6-17
Author(s):  
Amanbir kaur Chahal ◽  
Gurpreet Singh
Keyword(s):  
Cloud Computing ◽  
Business Processes ◽  
Service Oriented Architecture ◽  
Third Party ◽  
The Internet ◽  
It Services ◽  
Service Oriented ◽  
High Bandwidth ◽  
Use Of The Internet ◽  
Definition Of

In this paper we will discuss Outsourcing is the commissioning of a third party (or a number of third parties) to manage a client organization.s IT assets, people and/ or activities to required results. Business process outsourcing (BPO) is a more comprehensive definition of the current situation within the outsourcing domain. BPO has become increasingly interesting as more and more business processes are commoditized and thus easier to be hosted by an external party. Cloud Computing has all the attributes and potential to support a global BPO environment. These attribute are: virtualization, service oriented architecture (SOA), utility based pricing and grid computing. Cloud Computing involves the movement of IT services . application, infrastructure and platform . onto the Internet and deployment models. Because of the high availability, high bandwidth and the increased use of the Internet it has become easier to access a variety of services, traditionally originating from within a company.s data center.

scholarly journals ESTIMATION OF THE WORKLOAD OF A HYBRID COMPUTING CLUSTER IN TASKS OF MODELING IN MATERIALS SCIENCE

2020 ◽  
Author(s):  
Konstantin Volovich
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Materials Science ◽  
Cluster Performance ◽  
Computing Systems ◽  
Hybrid Computing ◽  
Methods Of Calculation ◽  
Roofline Model ◽  
Performance Computing

The article is devoted to methods of calculation and evaluation of the effectiveness of the functioning of hybrid computing systems. The article proposes a method of calculating the value of the workload using peak values of the cluster performance. The results and the quality of the functioning of cloud scientific services of high-performance computing using the roofline model are analyzed.

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