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In most parallel algorithms, UEs need to exchange information as the computation proceeds Shared memory environments provide this capability by default, and the challenge in these systems is to synchronize access to shared memory so that the results are correct regardless of how the UEs are scheduled In distributed memory systems, however, it is the other way around: Because there are few, if any, shared resources, the need for explicit synchronization to protect these resources is rare Communication, however, becomes a major focus of the programmer's effort 641 Message Passing A message is the most basic communication element A message consists of a header containing data about the message (for example, source, destination, and a tag) and a series of bits to be communicated Message passing is typically two sided, meaning that a message is explicitly sent between a pair of UEs, from a specific source to a specific destination In addition to direct message passing, there are communication events that involve multiple UEs (usually all of them) in a single communication event We call this collective communication These collective communication events often include computation as well, the classic example being a global summation where a set of values distributed about the system is summed into a single value on each node In the following sections, we will explore communication mechanisms in more detail We start with basic message passing in MPI, OpenMP, and Java Then, we consider collective communication, looking in particular at the reduction operation in MPI and OpenMP We close with a brief look at other approaches to managing communication in parallel programs

Once you have Typica and its dependencies in your classpath, there are several source code-level steps required for the snippets to runYou need the following three import statements:

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CORBA has been designed from the ground up to support a wide range of network, operating system, and language configurations This makes it, for some purposes, a more attractive solution than RMI, which is limited primarily to the Java platform While not hardware or operating system specific, it is still fairly language specific unless you use a bridge from Java to another language, which requires considerable effort CORBA, on the other hand, is not limited to invoking objects running within a JVM It is not a language per se, but a specification for how objects will interact Thus, it is not limited to a single language CORBA services and clients can be written in a variety of languages Suppose you wanted to write a business object that would fulfill requests for a range of machine types, and that would integrate with almost any major programming language such as C++ and Java CORBA would be an ideal solution, as it does not lock the developer into a single language for development and use of the business object That's the purpose behind the CORBA vision to make objects accessible from any language and platform Older legacy systems can be integrated with Java software and revitalized (for example, adding on a Web interface to an old inventory management system) The ability to interconnect with existing legacy systems isn't the only factor in CORBA's favor though CORBA makes a good choice for Java developers, not just now but also in the future Languages of the future that supercede Java will still be able to communicate with "legacy" systems that we are now writing and will write in the future Consider it a way to make your systems "future-proof" While CORBA itself is not a language, it introduces a new language CORBA services are described by a schema, which is a template for the methods an object makes available Such schemas are expressed using the Interface Definition Language (IDL) Languages like Java that support CORBA can implement an IDL schema, thus allowing other software to invoke methods.

Message passing between a pair of UEs is the most basic of the communication operations and provides a natural starting point for our discussion A message is sent by one UE and received by another In its most basic form, the send and the receive operation are paired As an example, consider the MPI program in Fig 611 and 612 In this program, a ring of processors work together to iteratively compute the elements within a field (field in the program) To keep the problem simple, we assume the dependencies in the update operation are such that each UE only needs information from its neighbor to the left to update the field We show only the parts of the program relevant to the communication The details of the actual update operation, initialization of the field, or even the structure of the field and boundary data are omitted The program in Fig 611 and 612 declares its variables and then initializes the MPI environment This is an instance of the SPMD pattern where the logic within the parallel algorithm will be driven by the process rank ID and the number of processes in the team After initializing field, we set up the communication pattern by computing two variables, left

import javautil*; import comxeroxamazonwscommon*; import comxeroxamazonwssdb*;

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