MAPCITE Supercharged with NVIDIA CUDA Parallel Processing

As datasets multiply and grow increasingly larger in size, it becomes more difficult for our analysts, actuaries and users to effectively explore data and make the decisions that directly affect the business. It’s not uncommon to see data wait times ranging from minutes to hours. Immediacy has become difficult to achieve across increasingly large and complex datasets with traditional CPU computing technology. MAPCITE has successfully integrated GPU computing technology into the enterprise software platform.

So what is GPU (Graphics Processing Units) computing?

Originally designed to improve the quality and speed of video gaming, GPU's have started to gain acceptance in the commercial world of computing, especially where there are problems requiring multiple repetitive tasks on very large datasets in very small amounts of time. MAPCITE employs GPU computing to ingest massive datasets and blend together with other similarly large datasets to deliver highly complex and hugely time consuming Location Analytics in near real time. Simply put it’s like having a supercomputer in a server.

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Insurance and Mortgage Risk, Under and Over Exposure...

Where is my business under or over exposed? Where exactly are my insured assets? What are their proximities to risk? Is my mortgage book at risk due to natural or man-made perils? How many houses with mortgages are in flood areas or over old disused coal mines?

These are the typical types of questions we are increasingly being asked to help solve. If your business has multiple and large volumes of complex products, then they will almost definitely have a location element which you will have never been able to include in your risk computations. Yet it’s this location element that hides the most risk.

Imagine the ability to measure many various complex risks simultaneously, such as the natural catastrophes opposite, and, with the click of a button, answer the CEO or the markets question..."What is my risk profile looking like today or better still at this moment in time"?

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