Abstract—Analytical workloads abound in application do-mains ranging from computational finance and risk analytics to engineering and manufacturing settings. In this paper we describe a Platform for Parallel R-based Analytics on the Cloud (P2RAC). The goal of this platform is to allow an Analyst to take a simulation or optimization job (both the code and associated data) that runs on their personal workstations and with minimum effort have them run on large-scale parallel cloud infrastructure. If this can be facilitated gracefully, an Analyst with strong quantitative but perhaps more limited development skills can harness the computational power of the cloud to solve larger analytically problems in less time. P2RAC is currently designed for...
1) Numéro d’ordre a ̀ demander au Bureau de l’École Doctorale avant le tirage définitif de la the...
Cloud computing, with its promise of virtually infinite resources, seems to suit well in solving res...
User analysis job demands can exceed available computing resources, especially before major conferen...
This paper addresses the problem of harnessing cloud-based infrastructure for the kind of analytical...
Translation of Data analysis algorithms from data analysis language to high-level programming langua...
Large-scale data management and deep data analysis are increasingly important for both enterprise an...
Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and...
Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the nee...
Abstract—Large-scale ad hoc analytics of genomic data is popular using the R-programming language su...
The Amazon Elastic Compute Cloud (EC2)is a service providing on-demand compute capacity to the publi...
Abstract—Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminat...
The massively increasing amount of often geographically dispersed large quantities of data of experi...
It's tough to argue with R as a high-quality, cross-platform, open source statistical software produ...
High Performance Computing (HPC) enables significant progress in both science and industry. Whereas ...
Cloud Computing constitutes a model capable of enabling the network access in a shared, practical an...
1) Numéro d’ordre a ̀ demander au Bureau de l’École Doctorale avant le tirage définitif de la the...
Cloud computing, with its promise of virtually infinite resources, seems to suit well in solving res...
User analysis job demands can exceed available computing resources, especially before major conferen...
This paper addresses the problem of harnessing cloud-based infrastructure for the kind of analytical...
Translation of Data analysis algorithms from data analysis language to high-level programming langua...
Large-scale data management and deep data analysis are increasingly important for both enterprise an...
Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and...
Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the nee...
Abstract—Large-scale ad hoc analytics of genomic data is popular using the R-programming language su...
The Amazon Elastic Compute Cloud (EC2)is a service providing on-demand compute capacity to the publi...
Abstract—Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminat...
The massively increasing amount of often geographically dispersed large quantities of data of experi...
It's tough to argue with R as a high-quality, cross-platform, open source statistical software produ...
High Performance Computing (HPC) enables significant progress in both science and industry. Whereas ...
Cloud Computing constitutes a model capable of enabling the network access in a shared, practical an...
1) Numéro d’ordre a ̀ demander au Bureau de l’École Doctorale avant le tirage définitif de la the...
Cloud computing, with its promise of virtually infinite resources, seems to suit well in solving res...
User analysis job demands can exceed available computing resources, especially before major conferen...