6 posts found under,

gpus

The MapD Immerse visual analytics client has a core feature we refer to as crossfilter, which allows a filter applied to one chart to simultaneously be applied to the rest of the charts on a dashboard. This provides a natural interface for data exploration, allowing a multi-dimensional view of data even as a user drills deep into a dataset. From a technical perspective, crossfiltering is not difficult (on the surface). Behind each Immerse chart is a SQL statement. When an e... read more

This post first appeared as a byline on The Next Platform in May of 2016. Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter. This movement is led by Google, Facebook, Amazon, Microsoft, Tesla, Baidu and others who have quietly but rapidly shifted their hardware philosophy over the past twelve months. Each of these companies have significantly upgraded their investment in GPU hardware and in doing so have put leg... read more

A few years back, the American Statistical Association put out a dataset of hundreds of millions of US airline flights from 1987 to 2008, as part of a supercomputing competition. The dataset includes every single flight record known by Bureau of Transportation Statistics for that two decade period; every prop plane, every jet plane, balloon or blimp. We wanted to put the MapD database and visualization software through its paces, as well as help you figure out whether your l... read more

While we love datasets of all shapes and sizes at MapD, Twitter holds a special place in our hearts. This is perhaps because we find Twitter data to be almost peerless among public datasets in its ability to provide a glimpse into the human experience - revealing what people are saying when and where. Twitter is powerful in that it provides insight into a wide variety of social phenomena both at the level of individual tweets as well as rolled up by user, geography or topic/... read more

Note: The following post was originally published on June 23, 2015 on Nvidia's Parallel ForAll blog. This is only an excerpt, you can find the full original here. Co-written by Alex Suhan and Todd Mostak of MapD. At MapD our goal is to build the world’s fastest big data analytics and visualization platform that enables lag-free interactive exploration of multi-billion row datasets. MapD supports standard SQL queries as well as a visualization API that maps OpenGL primitives... read more

MapD is a next-generation data analytics platform designed to process billions of records in milliseconds using GPUs. It features a relational database backend with advanced visualization and analytic features to enable hyper-interactive exploration of large datasets. The inspiration for MapD came from our own struggles wrestling with big data, marked by frustrating encounters with tempermental clusters and overnight queries. Such "data trauma" is rampant. Even though our... read more