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Parallel Computing
Published in Sanjay Saxena, Sudip Paul, High-Performance Medical Image Processing, 2022
Biswajit Jena, Pulkit Thakar, Gopal Krishna Nayak, Sanjay Saxena
Message Passing: It refers to the passing of messages from one process to another. There are mainly two different message passing modes: synchronous and asynchronous. Synchronous message passing includes the passing of messages between two processes where the receiver must be ready to receive the message. In an asynchronous mode the receiver is not ready for receiving the message. In here the processes assigned to a single processor might be more than on. The processes that need to send or receive data use certain instruction. For example, we can consider synchronous mode and the instructions used to send and receive data could be send() and receive(), respectively. As it is synchronous mode, every receive() instruction needs a send() instruction. This is illustrated in Figure 2.11.
Parallel and Distributed Processing
Published in David R. Martinez, Robert A. Bond, Vai M. Michael, High Performance Embedded Computing Handbook, 2018
Albert I. Reuther, Hahn G. Kim
Because message passing supports nearly any type of parallel processor architecture, it has become the most widely used programming model for large-scale applications. Messaging passing’s partitioned address space, though, places the burden of partitioning and communicating data between processors on the user. Programmers naturally think of a dataset as a single array rather than multiple subarrays. Transitioning from a global address space to a partitioned address space is not trivial.
Distributed and Parallel Computing
Published in Sunilkumar Manvi, Gopal K. Shyam, Cloud Computing, 2021
Sunilkumar Manvi, Gopal K. Shyam
Message passing: It is a type of communication between processes. Message passing is a form of communication used in parallel programming and object-oriented programming. Communications are completed by the sending of messages (functions, signals and data packets) to recipients.
Programming models and systems for Big Data analysis
Published in International Journal of Parallel, Emergent and Distributed Systems, 2019
Loris Belcastro, Fabrizio Marozzo, Domenico Talia
The message passing model is a well-known paradigm that provides the basic mechanisms for process-to-process communication in distributed computing systems where each processing element has its own private memory. In message passing the sending process composes the message containing the data to share with the receiving process(es) including a header specifying to which processing element and process the data is to be routed, and sends it to the network. Once the message has been inserted in the communication network, generally the sending process continues its execution (see Figure 5). This kind of send is called a non-blocking send. The receiving process must be aware that it is expecting data. It indicates its readiness to receive a message by executing a receive operation. If the expected data has not yet arrived, the receiving process suspends (blocks) until it does. Thus, the primitives of message passing model are basically two: Send(destination, message): a process sends a message to another process identified as destination;Receive(source, message): a process receives a message from another process identified as source.Message passing is used in many programming languages, operating systems and library for supporting data communication. Among those, the Message Passing Interface (MPI) is the most used library for programming message passing applications on distributed-memory parallel systems. Although MPI library has been largely used as a general parallel programming model, recently it has been exploited for implementing Big Data applications with positive results in terms of programmability and scalability [14–16].