Risk Management Solutions (RMS) will bring high-performance computing (HPC) to the industry through its new Enterprise Grid Computing software. Enterprise Grid Computing, which fully integrates the RMS RiskLink modeling platform with Microsoft’s Windows HPC Server, is designed to enable computing resources to be used much more efficiently across the organization, with more flexible job and resource management and faster analysis run times providing higher productivity and deeper insight into modeled results.

Enterprise Grid Computing is an optional and separately licensed component of the RMS product suite to be released with version 10.0 of RMS’ catastrophe modeling software. Major technology and infrastructure advancements in the latest version of RMS RiskLink and RiskBrowser also will deliver performance and scalability improvements, significantly increasing efficiency and reducing model runtimes, RMS says.

Working closely with Microsoft, RMS is the first cat modeler to have developed a solution specifically designed for a high-performance computing environment, the company says. By constructing large-scale computing grids that overcome bottlenecks for high volumes of data and analytics, RMS says Enterprise Grid Computing enables insurers and reinsurers to match their computing resources ‘on demand’ to users and jobs that create the biggest impact on the business. With Enterprise Grid Computing, run times can be significantly reduced, enabling companies to gain more up-to-date views of portfolio risk and a near real-time understanding of modeled losses. Advanced job management capabilities also allow the most critical jobs to preempt lower priority jobs that are already running.

RMS also asserts that Enterprise Grid Computing insurers and reinsurers also will be able to run more analytical cycles and process higher quantities of data, enabling them to gain insights into their portfolios at the point of decision-making and test assumptions used in RMS models, as well as in their own portfolio exposure data.

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