Split-Second Data Mapping

by Rob Matheson, MIT News

People generally associate graphic processing units (GPUs) with imaging processing. Developed for video games in the 1990s, modern GPUs are specialized circuits with thousands of small, efficient processing units, or “cores,” that work simultaneously to rapidly render graphics on screen.

But for the better part of a decade, GPUs have also found general computing applications. Because of their incredible parallel-computing speeds and high-performance memory, GPUs are today used for advanced lab simulations and deep-learning programming, among other things.

Now a new database-analytics platform leverages graphics-processing units (GPUs) to process billions of data points in milliseconds. MapD was developed by Todd Mostak, a former researcher at the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory.

In addition to processing data faster than traditional database management systems, MapD visualizes all processed data points nearly instantaneously — such as, say, plotting tweets on a world map — and parameters can be modified on the fly to adjust the visualized display.

In most implementations of GPU-powered databases, the data is stored initially on a central-processing unit (CPU), transferred to the GPU for a query, and results are moved to the CPU for storage. Instead of storing data on CPUs, MapD caches as much data as possible on multiple GPUs. If a database needs to query the same data point repeatedly, it can access that data point in the GPU’s random-access memory.

In a recent test, the system analyzed a 1.2-billion-record New York City taxi dataset. MapD ran 74 times faster than several advanced CPU database systems and completed several queries within milliseconds.

With its first product launched last March, MapD’s clients already include Verizon and other big-name telecommunications companies, a social media giant, and financial and advertising firms. In October, the investment arm of the U.S. Central Intelligence Agency, In-Q-Tel, announced that it had invested in MapD’s latest funding round to accelerate the development of certain features for the U.S. intelligence community.

“[The CIA has] a lot of geospatial data, and they need to be able to form, visualize, and query that data in real-time. It’s a real need across the intelligence community,” Mostak says. Read the article

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