With the development of hardware, lower prices for hardware and the huge amounts of data in daily work, systems for High Performance Computing have become greatly expanded. Even Microsoft, with its cluster management programming environment called Windows HPC Server 2008, set foot in the field of High Performance Computing. In this thesis we describe the installation process of Windows HPC Server 2008 on a cluster of computers, its configuration, monitoring and diagnostic tools and user interface. The installation and configuration of the system is very simple, installation is supported with wizard and a list of necessary tasks for system configuration. The user interface is well designed and intuitive, and greatly contributes to the usability and transparency of the system. Here we introduced the possibility of different implementations for distributed computing applications on the case of applications for the calculation of π number. In the second part of the thesis we tested capabilities of Windows HPC Server 2008 on two cases of text documents classification, using a method called Support Vector Machines (SVM). We compared these results with the results of text documents classification within Condor environment. It turns out that Windows HPC Server 2008 is faster then Condor environment when processing small amounts of data, when processing large amounts of data Condor environment provides better results.