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Dataflow
In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataflow computing is a software paradigm based on the idea of representing computations as a directed graph, where nodes are computations and data flow along the edges. Dataflow can also be called stream processing or reactive programming. 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 programmi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Modular Dataflow Machine
Binary Modular Dataflow Machine (BMDFM) is a software package that enables running an application in parallel on shared memory symmetric multiprocessing (SMP) computers using the multiple processors to speed up the execution of single applications. BMDFM automatically identifies and exploits parallelism due to the static and mainly ''dynamic scheduling'' of the dataflow instruction sequences derived from the formerly sequential program. The BMDFM dynamic scheduling subsystem performs a symmetric multiprocessing (SMP) emulation of a ''tagged-token dataflow machine'' to provide the transparent dataflow semantics for the applications. No directives for parallel execution are needed. Background Current parallel shared memory SMPs are complex machines, where a large number of architectural aspects must be addressed simultaneously to achieve high performance. Recent commodity SMP machines for technical computing can have many tightly coupled cores (good examples are SMP machines b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dataflow Programming
In computer programming, dataflow programming is a programming paradigm that models a program as a directed graph of the data flowing between operations, thus implementing dataflow principles and architecture. Dataflow programming languages share some features of functional languages, and were generally developed in order to bring some functional concepts to a language more suitable for numeric processing. Some authors use the term ''datastream'' instead of '' dataflow'' to avoid confusion with dataflow computing or dataflow architecture, based on an indeterministic machine paradigm. Dataflow programming was pioneered by Jack Dennis and his graduate students at MIT in the 1960s. Considerations Traditionally, a program is modelled as a series of operations happening in a specific order; this may be referred to as sequential, procedural, control flow (indicating that the program chooses a specific path), or imperative programming. The program focuses on commands, in line with the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dataflow Architecture
Dataflow architecture is a dataflow-based computer architecture that directly contrasts the traditional von Neumann architecture or control flow architecture. Dataflow architectures have no program counter, in concept: the executability and execution of instructions is solely determined based on the availability of input arguments to the instructions, so that the order of instruction execution is unpredictable, i.e., behavior is nondeterministic. Although no commercially successful general-purpose computer hardware has used a dataflow architecture, it has been successfully implemented in specialized hardware such as in digital signal processing, network routing, graphics processing, telemetry, and more recently in data warehousing, and artificial intelligence (as: polymorphic dataflow Convolution Engine, structure-driven, dataflow scheduling). It is also very relevant in many software architectures today including database engine designs and parallel computing frameworks. Sync ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-flow Analysis
In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataflow computing is a software paradigm based on the idea of representing computations as a directed graph, where nodes are computations and data flow along the edges. Dataflow can also be called stream processing or reactive programming. 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 ab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stream Processing
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views data streams, or sequences of events in time, as the central input and output objects of computation. Stream processing encompasses dataflow programming, reactive programming, and distributed data processing. Stream processing systems aim to expose parallel processing for data streams and rely on streaming algorithms for efficient implementation. The software stack for these systems includes components such as programming models and query languages, for expressing computation; stream management systems, for distribution and scheduling; and hardware components for acceleration including floating-point units, graphics processing units, and field-programmable gate arrays. The stream processing paradigm simplifies parallel software and hardware by restricting the parallel computation that can be performed. G ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stream Processing
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views data streams, or sequences of events in time, as the central input and output objects of computation. Stream processing encompasses dataflow programming, reactive programming, and distributed data processing. Stream processing systems aim to expose parallel processing for data streams and rely on streaming algorithms for efficient implementation. The software stack for these systems includes components such as programming models and query languages, for expressing computation; stream management systems, for distribution and scheduling; and hardware components for acceleration including floating-point units, graphics processing units, and field-programmable gate arrays. The stream processing paradigm simplifies parallel software and hardware by restricting the parallel computation that can be performed. G ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem. History Google Cloud Dataflow was announced in June, 2014 and released to the general public as an open beta in April, 2015. In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs ( data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. The donated code formed the original basis for Apache Beam. References External links * Dataflow In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataf ... Cloud computing {{Google-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Power BI
Power BI is an interactive data visualization software product developed by Microsoft with a primary focus on business intelligence. It is part of the Microsoft Power Platform. Power BI is a collection of software services, apps, and connectors that work together to turn unrelated sources of data into coherent, visually immersive, and interactive insights. Data may be input by reading directly from a database, webpage, or structured files such as spreadsheets, CSV, XML, and JSON. General Power BI provides cloud-based BI (business intelligence) services, known as "Power BI Services", along with a desktop-based interface, called "Power BI Desktop". It offers data warehouse capabilities including data preparation, data discovery, and interactive dashboards. In March 2016, Microsoft released an additional service called Power BI Embedded on its Azure cloud platform. One main differentiator of the product is the ability to load custom visualizations. History This application was ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arvind (computer Scientist)
Arvind is the Johnson Professor of Computer Science and Engineering in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). He was also elected as a member into the National Academy of Engineering in 2008 for contributions to data flow and multi-thread computing and the development of tools for the high-level synthesis of hardware. Career Arvind's research interests include formal verification of large-scale digital systems using Guarded Atomic Actions, Memory Models, and Cache Coherence Protocols for parallel architectures and languages. Past work was instrumental in the development of dynamic dataflow architectures, two parallel computing programming languages (''Id'' and ''pH''), and the compiling of such languages on parallel machines. At IIT Kanpur, he earned a Bachelor of S ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kahn Process Networks
A Kahn process network (KPN, or process network) is a distributed ''model of computation'' in which a group of deterministic sequential processes communicate through unbounded first in, first out channels. The model requires that reading from a channel is blocking while writing is non-blocking. Due to these key restrictions, the resulting process network exhibits deterministic behavior that does not depend on the timing of computation nor on communication delays. Kahn process networks were originally developed for modeling parallel programs, but have proven convenient for modeling embedded systems, high-performance computing systems, signal processing systems, stream processing systems, dataflow programming languages, and other computational tasks. KPNs were introduced by Gilles Kahn in 1974. Execution model KPN is a common model for describing signal processing systems where infinite streams of data are incrementally transformed by processes executing in sequence or paralle ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Cleansing
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting or a data quality firewall. After cleansing, a data set should be consistent with other similar data sets in the system. The inconsistencies detected or removed may have been originally caused by user entry errors, by corruption in transmission or storage, or by different data dictionary definitions of similar entities in different stores. Data cleaning differs from data validation in that validation almost invariably means data is rejected from the system at entry and is performed at the time of entry, rather than on batches of data. The actual proc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-flow Diagram
A data-flow diagram is a way of representing a flow of data through a process or a system (usually an information system). The DFD also provides information about the outputs and inputs of each entity and the process itself. A data-flow diagram has no control are no decision rules and no loops. Specific operations based on the data can be represented by a flowchart. There are several notations for displaying data-flow diagrams. The notation presented above was described in 1979 by Tom DeMarco as part of structured analysis. For each data flow, at least one of the endpoints (source and / or destination) must exist in a process. The refined representation of a process can be done in another data-flow diagram, which subdivides this process into sub-processes. The data-flow diagram is a tool that is part of structured analysis and data modeling. When using UML, the activity diagram typically takes over the role of the data-flow diagram. A special form of data-flow plan is a site-o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
