The fully integrated environment supports co-simulation, debug and trace, high-speed simulation and distributed processing software over multiple SoCs (System-on-Chips) and MCUs (Microcontrollers ...

Incredibuild, an Israeli startup that provides a way for organizations to implement distributed computing architecture to speed up the processing needed for intensive tasks like software ...

Renesas launched a new integrated development environment that allows engineers to rapidly create software for automotive ECUs with multiple devices.

Renesas is developing a “ Distributed Processing Software for Multi-devices ” (Multi-Device Framework) to solve the above issues (figure 2). This software can maximize the performance of hardware by ...

Stephan Ewen talks about how Apache Flink handles stateful stream processing and how to manage distributed stream processing & data driven applications efficiently with Flink's checkpoints&savepoints.

Hazelcast, a provider of an open source in-memory data grid (IMDG) platform, is unveiling Hazelcast Jet, a new platform that gives users a distributed processing engine for big data streams. With ...

Vantiq, Inc. announced that the company has been granted a U.S. patent for “deployment of an event-driven application in an IoT environment.” ...

Advantages of Distributed Data Processing. Distributed data processing is a computer-networking method in which multiple computers across different locations share computer-processing capability.

In this video from the European R Users Meeting, Henrik Bengtsson from the University of California San Francisco presents: A Future for R: Parallel and Distributed Processing in R for Everyone. "The ...

Also known as "distributed logic," distributed intelligence refers to separating the processing in a large system into multiple subsystems or extracting certain functions from the main system and ...