Search Results for "cluster 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 query workloads. ...

A framework to run MATLAB programs as batch jobs. Features a structured input description, integrity constraints and GUI.Independent parts of a job can execute in parallel on a cluster computer. Developed at Freiburg Brain Imaging (FBI) - http://fbi.uniklinik-freiburg.de/

Summingbird is a streaming + batch hybrid computation framework developed by Twitter. Its aim is to let developers express data aggregation pipelines in a unified way, where the same logic can run either in real time (stream) or in batch mode, and the results can be merged or reconciled. In effect, Summingbird abstracts over multiple execution engines (such as Storm, Scalding, etc.) to provide one high-level program that composes transformations and aggregations, and then executes them in...

Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster