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May 14, 2008
When you're the inventor of one of the most successful and influential programming languages of the last decade, what do you do for an encore? Judging by demos at the recent JavaOne conference, if you're Sun Microsystems, you invent another programming language. But Fortress is more than just another syntax to remember. Instead, Sun Labs is taking lessons learned from Java and applying them to the thornier problems of application development for HPC. If it succeeds, Fortress could become the language of choice for the new computing era.
Full story at InfoWorld
While the Microsoft juggernaut has been touting the joys of its new Windows HPC Server 2008, the Linux HPC contingent has been somewhat less vocal of late. But now Red Hat has come up with its version of an integrated cluster solution.
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Even though the cost of servers still dominates the datacenter budget, storage is actually on a steeper growth curve. HPC storage, in particular, is being singled out as high-growth opportunity. Vendors are scrambling to keep up.
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Google datacenters most energy efficient; Cluster Resources to demo Moab Hybrid Cluster; Red Hat Linux releases HPC distro. John West recaps those stories and more in our weekly wrap-up.
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Sep 04 | | Disk drives are approximately 250 times denser today than a decade ago. This is good news for users who are creating, manipulating and storing more data than ever before. It gives them an opportunity to derive more value from their stored data and lowers the capital acquisition and operating expense associated with that data.
BlueArc's Titan architecture represents an evolutionary step in file servers by creating a hardware-based file system that can scale bandwidth, IOPS, and overall data capacity well beyond conventional software-based devices. With its ability to virtualize a massive storage pool of up to four usable petabytes of tiered storage, Titan can scale with growing data requirements, offering a competitive advantage for businesses, researchers, or other enterprises seeking to better manage data growth while still ensuring optimal performance.
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