Problems of high-performance processing of mass cluster data are considered. Estimates of execution times of parallel data processing programs and a heuristic algorithm of optimization of cluster architectures for such problems are proposed.

Both grid and cloud are used to organize large scale calculations and data processing on remote computers. Grid which became a basic computing infrastructure for the Large Hadron Collider experiments provides unified technical solutions for sharing and merging distributed heterogeneous computing resources within big collaboration groups. Cloud became popular among data centers and computing service providers because of flexibility, manageability and efficient hardware utilization. Both approaches share common ideology "computing as a service", so one can expect additional benefits from their integration.The paper describes our approach to the integration. We propose to use cloud within grid sites for acceleration of application deployment and easy support of multiple virtual organizations by grid sites.The cloud in grid approach has been implemented and tested in Ukrainian National Grid, a part of European Grid Infrastructure.

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