Video games, high resolution pictures, and even our computers wouldn’t be the same without GPUs. GPUs, or graphic processing units, are highly specialized bits of technology that render images onto our screens. First developed for video games, GPUs are also able to deal with non-graphic information for super high-speed information processing.
GPUs have extraordinary computing power, with high-performance memory and parallel-computing speeds allowing them to analyze a vast amount of information in a matter of seconds. GPUs can be used for advanced lab simulations and deep-learning programming. GPUs have now found a place in high-speed mapping, with a project called MapD.
MapD is unique because it has been designed to run on GPUs instead of CPUs, which are the traditional form of power for most database-management systems. With its GPU power, MapD can process billions of data points in milliseconds. The program can also provide a visual display, showing users virtually any set of information they have put in the computer.
MapD is currently being used by telecommunications companies, social media organizations, financial aid, and advertising firms. Other governmental agencies have also expressed interest in MapD’s future, as the technology can be utilized in a variety of ways. Improving GPU technology has been at the forefront of MapD’s goal, and it has done so in a way that changes how GPUs will be used in the future of computers and telecommunications.
One application that has been popular for MapD has been the ‘Tweetmap.’ The Tweetmap allows users to track certain hashtags around the world.
Another map that was created by MapD shows every political donation made in the United States, color coded for political party.
The program allows people with questions to be able to find up-to-date answers in seconds, if they can define their data set and query. The program has been expanded into its own company, and more technological advances are sure to come from the MapD team in the coming months.
Watch the video explaining MapD’s Tweetmap: