Dataflow
ftware architecture
Dataflow is a software paradigm based on the idea of disconnecting computational actors into stages (pipelines) that can execute concurrently. Dataflow can also be called stream processing or reactive programming.[1]
There have been multiple data-flow/stream processing languages of various forms (see Stream processing). Data-flow hardware (see Dataflow architecture) is an alternative to the classic Von Neumann architecture. The most obvious example of data-flow programming is the subset known as reactive programming with spreadsheets. As a user enters new values, they are instantly transmitted to the next logical "actor" or formula for calculation.
Distributed data flows have also been proposed as a programming abstraction that captures the dynamics of distributed multi-protocols. The data-centric perspective characteristic of data flow programming promotes high-level functional style of specifications, and simplifies formal reasoning about system components.
Hardware architecture
Hardware architectures for dataflow was a major topic in Computer architecture research in the 1970s and early 1980s. Jack Dennis of MIT pioneered the field of static dataflow architectures. Designs that use conventional memory addresses as data dependency tags are called static dataflow machines.
Content-addressable memory are called dynamic dataflow machines by Arvind. They use tags in memory to facilitate parallelism. Data flows around the computer through the components of the computer.
- SDF3 : Performance analysis tool for DataFlow Model
- Ruby Dataflow : Ruby gem adding Dataflow variable support
- Acar et al., Adaptive Functional Programming, POPL 2002
- Scala Dataflow : The Akka toolkit provides (among other things) dataflow concurrency in Scala
- GPars dataflow : A Groovy and Java concurrency framework
- Free Data Flow Templates: Free data flow templates for Keynote & PowerPoint presentations
- SaaS traceability solution that merge data connector to track activity on field (B2B solution)
- TensorFlow : Google's open source (Apache 2.0) second-generation Python and C++ machine learning library using dataflow graphs
- Apache Flink : An open-source stream processing framework based on the dataflow programming model[2]
References
- ^ A Short Intro to Stream Processing
- ^ Carbone, P., Katsifodimos, A., Ewen, S., Markl, V., Haridi, S. et al. (2015) Apache flink: Stream and batch processing in a single engine. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 36(4)