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Model-Based Clustering for Social Networks.
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SystemImager is software which automates Linux installs, software distribution, and production deployment. SystemImager makes it easy to do automated installs (clones), software distribution, content or data distribution, configuration changes, and operating system updates to your network of Linux machines. You can even update from one Linux release version to another! It can also be used to ensure safe production deployments. By saving your current production image before updating to your new production image, you have a highly reliable contingency mechanism. If the new production enviroment is found to be flawed, simply roll-back to the last production image with a simple update command! Some typical environments include: Internet server farms, database server farms, high performance clusters, computer labs, and corporate desktop environments.
Building and Promoting a Linux-based Operating System to Support Virtual Organizations for Next Generation Grids (2006-2010). The emergence of Grids enables the sharing of a wide range of resources to solve large-scale computational and data intensive problems in science, engineering and commerce. While much has been done to build Grid middleware on top of existing operating systems, little has been done to extend the underlying operating systems to enablee and facilitate Grid computing, for example by embedding important functionalities directly into the operating system kernel.
"For a while now, IBM has had multiple and competing tools for managing AIX and Linux clusters for its supercomputer customers and yet another set of tools that were used for other HPC setups with a slightly more commercial bent to them. But Big Blue has now cleaned house, killing off its closed-source Cluster Systems Management (CSM) tool and tapping its own open source Extreme Cluster Administration Toolkit (known as xCAT) as its replacement."
Modern graphics processing units (GPUs) contain hundreds of arithmetic units and can be harnessed to provide tremendous acceleration for many numerically intensive scientific applications. The key to effective utilization of GPUs for scientific computing
As high performance computing (HPC) becomes a ubiquitous part of the scientific computing landscape, the science of visualizing HPC datasets has become a critical field of its own. One of the hottest solutions can be found in commoditized high performance
J. Ko, B. Stewart, D. Fox, K. Konolige, and B. Limketkai. Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on, (27-31 Oct. 2003)