In May 2017, MapD along with H2O.ai and Continuum Analytics announced the GPU Open Analytics Initiative (GOAI), with the goal of accelerating end-to-end analytics and machine learning on GPUs. Adoption of GPUs for general purpose computing is a computing revolution driven by NVIDIA’s hardware innovations.
I recently came across Big Data Ball, an NBA stats distributor. They offered a dataset called: “NBA Play-By-Play Stats – 2004 to 2017”. It includes all events that occur in a game including: active lineups, shot distances, shot locations in X, Y coordinates, assists, time remaining, and tons of other interesting data points. Game on!
Today we are pleased to announce the release of 3.2.2 version of MapD. This release brings some key capabilities and performance improvements to both our interactive visual analytics client, MapD Immerse, and our GPU-accelerated SQL engine, MapD Core.
Our latest demo of MapD Core and MapD Immerse reveals the vast scope of marine activity around America’s shores–everything from the tracks of commercial freighters to the patrols of military vessels to the lazy patterns of pleasure boats out for a Sunday sail on San Francisco Bay.
Today, with great pride, MapD is announcing a partnership with the Harvard Center for Geographic Analysis (CGA).
We’re excited to announce our newest addition to the MapD executive team. Aaron Williams joins us today as VP of Global Community, responsible for fostering our growing developer, user and open source communities.
