Search Results for "spatial computing"

Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive...

VRTK is a collection of useful, reusable solutions to common problems found when building for virtual reality. VRTK aims to help productivity by speeding up the creation process from prototyping ideas to building complete solutions. The passion behind VRTK is to try and enable as many people as possible to build for VR, from seasoned developers to complete beginners who have a wonderful idea in their head but are unsure of how to create it. VRTK aims to be easy to understand so the absolute...

Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors.