Recent advancements in data intensive computing for science discovery are fueling a dramatic growth in use of data-intensive iterative computations. The utility computing model introduced by cloud computing combined with the rich set of cloud infrastructure services offers a very attractive environment for scientists to perform such data intensive computations. The challenges to large scale distributed computations on cloudsdemand new computation frameworks that are specifically tailored for cloud characteristics in order to easily and effectively harness the power ofclouds. The use of portable Parallel Programming incloud computing i.e High Performance Computing(HPC) can increase the efficiency ofCloud Computing.
INTRODUCTION
The current scientific computing landscape is vastly populated by the growing set of data-intensive Computations that require enormous amounts of computational as well as storage resources and novel distributed computing frameworks. The pay-as-you-go Cloud computing model provides an option for the computational and storage needs of such computations. The new generation of distributed computing frameworks such as MapReduce focuses on catering to the needs of such data-intensive computations.
CLOUD COMPUTING
Cloud computing is a term used to describe both a platform and type of application. A cloud computing platform dynamically provisions, configures, reconfigures, and deprovisions servers as needed. Servers in the cloud can be physical machines or virtual machines. Advanced clouds typically include other computing resources such as storage area networks (SANs), network equipment, firewall and other security devices.
Read More >> Portable Parallel Programming in Cloud and HPC.
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