Hpc Visualization with X3D (Michail Karpov)
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Hpc Visualization with X3D (Michail Karpov)

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Hpc Visualization with X3D (Michail Karpov) Hpc Visualization with X3D (Michail Karpov) Document Transcript

  • Introduction The first time I encountered a problem rendering workload for servers and storage, at atime when I worked as a System Administrator at Motorola. In the process of scientific development, I worked on these cluster architectures:Moscow State University: Blue Gene / P - 23.8 TFlops Linpack (378 place in the world Top500)- Multiplication of large matrices, working with graphics. Hardware-software complex T-ForgeMini on the basis of eight dual-core AMD Opteron processor and operating system MicrosoftWindows Compute Cluster Server 2003 at Lobachevsky State University of Nizhni Novgorod.Also - a 16-nuclear cluster running Windows HPC Server at Saint-Petersburg State PolytechnicalUniversity. To develop this product was chosen among MS Visual Studio 2008. Work underway onthe basis of 16-core cluster running Windows HPC Server 2008 (provided to PolytechnicUniversity by Intel), using the provided by Microsoft tools and libraries and the HPC Pack HPCSDK. The system can operate in two modes: the general analysis of the system and a detailedanalysis of the selected task.General analysis of the systemFor a general analysis of the system used the metaphor "molecule." The nodes are nodes in the cluster molecule, which are located around the nucleus. Colorof the kernels varies depending on the workload of the core tasks. Kernel size depends on thetotal amount of memory on a given nucleus. Molecule can rotate and zoom in. When approaching you can see the tasks performed on each of the nuclei. As the systemis running a lot of tasks, the user can specify rules for demonstration: to show the predefinedtasks, the highest priority, the most demanding. With increasing object attributes appear over theimage. Uses related support panel, are the properties of selected objects in a standardized (2d),well-read format. This system can be used to analyze the performance of parallel programs on networks ofclusters with different values of performance, memory cores, the speed of the task, and diskspace.
  • Detailed analysis of the selected taskWith detailed analysis of the problem using the metaphor "greenhouse". The user puts the necessary requirements for the task (choose the task, indicates thenucleus on which to run the task). After that, he is watching how of the main resources areloaded and used during program execution. These resources is memory cores, CPU and diskspace. It is necessary for testing tasks on different cores and determine bottlenecks, which maybe the queue for entry to the storage (or lack of space on it), lack of CPU time or memoryshortage on the nuclei. For a detailed analysis of the task will run several times with different parameters ofenvironmental software and technical environment (place to storedzhah, the number of coresallocated memory by the nuclei). The user can play each set of tests and to visually identifywhere in there is bottleneck.SummaryTwo modes of data analysisOnline or postmortem analysis of the program.Example of use You can clearly seen that one of the nuclei heavily loaded on the molecule, and multiplecores are idle. Then the user increases the molecule in the correct kernel and receivesinformation on the most resource-intensive tasks running on that kernel. After that, he can shiftpart of the tasks or subtasks to idle core at real-time."Entry points" into the system Several "entry points" into the system are used to fix certain parts of the systemarchitecture. The user selects these points and mark them in the work process. When the choiceis made, the user immediately finds himself in the part of the molecule, which made the previousmark (for example, considering the third core at the second node). To create such an analog user experience using a Web browser uses the X3D markup,which allows you to work with the "entry points" to do zoom and rotate the molecule.