scholarly journals On the Elasticity of Parallel Components in a Cloud of High Performance Computing Services

2019 ◽  
Author(s):  
Francisco Carvalho Junior ◽  
João Marcelo Alencar

Cloud computing offers virtually unlimited set of resources and flexibility to allocate them through elasticity. But cloud limitations, such as the complexity of configuration and environment dynamicity, may jeopardizes the assurance of QoS requirements. HPC Shelf is a cloud of HPC services that employs a component-oriented architecture to describe hardware and software resources of parallel computing systems. We design a framework for HPC Shelf that employ cloud elasticity concepts for keeping the values of QoS metrics of parallel computing systems inside an acceptable range, enabling adaptations to fulfill the QoS contract restrictions. In our evaluation, using a linear algebra application, we show how HPC Shelf takes advantage of cloud elasticity to reinforce QoS requirements, rectifying assumptions from ill-defined QoS models.

2017 ◽  
Vol 10 (13) ◽  
pp. 445
Author(s):  
Purvi Pathak ◽  
Kumar R

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.


2019 ◽  
Vol 27 (3) ◽  
pp. 263-267
Author(s):  
Alexander S. Ayriyan

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.


2019 ◽  
Vol 27 (3) ◽  
pp. 263-267
Author(s):  
Alexander S. Ayriyan

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.


2020 ◽  
Vol 14 ◽  

Typically, the constant changes in computers and communications technology led to the need of on-demand network access to a shared computing resources to reduce cost and time and this is known as Cloud computing, which delivers computing services to users as a pay-as-you-go manner by emerging several distributed and high performance computing concepts. The cloud makes reaching any information or source possible from anywhere eliminating the setup and instillation step such that the user and the hardware may co-exist in different places. This comes beneficial for the users or the small companies that cannot effort to pay for the hardware, storage or resources as the big companies. Many of the studies on cloud computing was dedicated to the performance efficiency of task scheduling. Scheduling is a wide concept and it is one of the most important issues that generally work on mapping tasks to appropriate resources efficiently and effectively using one or more strategy. This paper have reviewed and classified the most recent scheduling algorithms in cloud computing and gave examples on each.


Author(s):  
Alexander S. Ayriyan

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.


Author(s):  
Gennady Shvachych ◽  
Nina Rizun ◽  
Olena Kholod ◽  
Olena Ivaschenko ◽  
Volodymyr Busygin

The chapter analyzes the ways of development of high-performance computing systems. It is shown that a real breakthrough in mastering parallel computing technologies can be achieved by developing an additional (actually basic) level in the hierarchy of hardware capacities of multiprocessor computing systems of MPP-architecture, the personal computing clusters. Thus, it is proposed to create the foundation of the hardware pyramid of parallel computing technology in the form of personal computing clusters. It is shown that on the basis of multiprocessor information systems processing and control, the control systems are implemented for many industries: space industry, aviation, air defense and anti-missile defense systems, and many others. However, the production of multiprocessor information processing and control systems is hampered by high cost at all its stages. As a result, the total cost of the system often makes it as an inaccessible tool. The use of modern multiprocessor cluster systems would reduce the costs of its production.


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