Examples of using Grid computing in English and their translations into Greek
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Grid computing.
Other jobs related to grid computing neural networks.
Many countries around the world have invested heavily on the development of the Grid computing infrastructure.
I was familiar with Grid Computing, so I thought it was something similar and left it at that.
However, since 2000,the idea has resurfaced in new forms(see application service provider, grid computing, and cloud computing). .
Grid computing applies resources of many computers in a network to solve one problem at the time.
Andre jobs relateret til grid computing neural networks.
Grid computing is applying the resources of many computers in a network to a single problem at the same time.
Among the KPMG business process offerings running on AWS available today are the grid computing and client due diligence solutions.
And supercomputing and grid computing technologies aimed at solving energy saving and resource saving problems.
He adopts new approaches in geographical analysis, such as Artificial Intelligence(AI) andAgent-Based Modelling; and supports new computational paths, such as Grid Computing and large scale distributed modelling.
While grid computing also offers a similar facility for computing power, cloud computing isn't restricted to just that.
More recently, CERN has become a centre for the development of grid computing, hosting projects including the Enabling Grids for E-sciencE(EGEE) and LHC Computing Grid. .
Grid computing has been applied in a variety of areas such as particle physics, bio-informatics, finance, social science and manufacturing.
So we adopted an x86 architecture that would enable us to run large-scale grid computing, which allowed us to improve risk management for our derivatives businesses and products.
The term grid computing originated in the early 1990s as a metaphor for making computer power as easy to access as an electric power grid. .
It's a proof-of-concept to show what kinds of services you can offer via decentralized bitcoin-incentivized grid computing and how they are qualitatively different from- and complementary to- what you can get from centralized cloud computing.”.
Utilize grid computing technologies and cloud computing to design applications and services based on the dynamic user requirements.
The research interests of the faculty in the computer architecture and high-performance computing area span computer architecture, parallel processing, cloud computing, and high-performance and grid computing.
The Workshop"Integrated Research in Grid Computing" will be held on April 2-4 2008 at the Creta Maris resort hotel at the seaside village of Hersonissos.
The grid computing solution provides organisations with on-demand access to computing capacity, providing a cost-effective way to conduct complex analyses of large data sets without the need for on-premises data centers or infrastructure.
Concurrency control in Database management systems(DBMS; e.g., Bernstein et al. 1987, Weikum and Vossen 2001), other transactional objects, andrelated distributed applications(e.g., Grid computing and Cloud computing) ensures that database transactions are performed concurrently without violating the data integrity of the respective databases.
One of the main strategies of grid computing is using software to divide and apportion pieces of a program among several computers, sometimes up to many thousands.
The grid computing solution provides organisations with on-demand access to computing capacity, providing a cost-effective way to conduct complex analyses of large data sets without the need for on-premises data centers or infrastructure.
The past few years have witnessed that Grid computing is evolving as a promising large-scale distributed computing infrastructure for scientists and engineers around the world to share various resources on the Internet including computers, software, data, instruments.
The grid computing solution provides organizations, such as those in financial services or healthcare, with on-demand access to computing capacity, providing a cost-effective way to conduct complex analyses of large data sets without the need for on-premises data centers or infrastructure.