This paper describes a service-oriented architecture that eases the process of scientific application deployment and execution in IaaS Clouds, with a focus on High Throughput Computing applications. The system integrates i) a catalogue and repository of Virtual Machine Images, ii) an application deployment and configuration tool, iii) a meta-scheduler for job execution management and monitoring. The developed system significantly reduces the time required to port a scientific application to these computational environments. This is exemplified by a case study with a computationally intensive protein design application on both a private Cloud and a hybrid three-level infrastructure (Grid, private and public Cloud).The authors wish to thank t...
High performance computing refers to the practice of aggregating computing power in a way that deliv...
Abstract Cloud computing evolved from the concept of utility computing, which is defined as the prov...
Cloud based scientific data management - storage, transfer, analysis, and inference extraction - is ...
This book presents a range of cloud computing platforms for data-intensive scientific applications. ...
Trabajo presentado al EGI Community Forum, celebrado en Bari (Italia) del 10 al 13 de noviembre de 2...
This paper presents a platform that supports the execution of scientific applications covering diffe...
International audienceCloud computing has evolved as a popular computing infrastructure for many app...
Cloud computing provides access to a large scale set of readily available computing resources at the...
The rise of virtualized and distributed infrastructures has led to new challenges to accomplish the ...
Abstract — The widely discussed scientific data deluge creates not only a need to computationally s...
The potential of cloud computing is still underutilised in the scientific computing field. Even if c...
Often, there is a particular type of applications in different scientific domains, i.e. non-interact...
Recently cloud services have been evaluated by scientific communities as a viable solution to satisf...
AbstractRunning computational science applications on the emerging cloud infrastructures requires ap...
Often, there is a particular type of applications in different scientific domains, i.e., non-interac...
High performance computing refers to the practice of aggregating computing power in a way that deliv...
Abstract Cloud computing evolved from the concept of utility computing, which is defined as the prov...
Cloud based scientific data management - storage, transfer, analysis, and inference extraction - is ...
This book presents a range of cloud computing platforms for data-intensive scientific applications. ...
Trabajo presentado al EGI Community Forum, celebrado en Bari (Italia) del 10 al 13 de noviembre de 2...
This paper presents a platform that supports the execution of scientific applications covering diffe...
International audienceCloud computing has evolved as a popular computing infrastructure for many app...
Cloud computing provides access to a large scale set of readily available computing resources at the...
The rise of virtualized and distributed infrastructures has led to new challenges to accomplish the ...
Abstract — The widely discussed scientific data deluge creates not only a need to computationally s...
The potential of cloud computing is still underutilised in the scientific computing field. Even if c...
Often, there is a particular type of applications in different scientific domains, i.e. non-interact...
Recently cloud services have been evaluated by scientific communities as a viable solution to satisf...
AbstractRunning computational science applications on the emerging cloud infrastructures requires ap...
Often, there is a particular type of applications in different scientific domains, i.e., non-interac...
High performance computing refers to the practice of aggregating computing power in a way that deliv...
Abstract Cloud computing evolved from the concept of utility computing, which is defined as the prov...
Cloud based scientific data management - storage, transfer, analysis, and inference extraction - is ...