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Socket class, it becomes almost as simple to write servers as it does clients The only difference between a server and a client is that the server binds to a specific port, using a ServerSocket object This ServerSocket object acts as a factory for client connections you don't need to create instances of the Socket class yourself These connections are modeled as a normal socket, so you can connect input and output filter streams (or even a reader and writer) to the connection

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Once a server socket is created, it will be bound to a local port and ready to accept incoming connections When clients attempt to connect, they are placed into a queue Once all free space in the queue is exhausted, further clients will be refused Constructors The simplest way to create a server socket is to bind to a local address, which is specified as the only parameter, using a constructor For example, to provide a service on port 80 (usually used for Web servers), the following snippet of code would be used:

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An important issue to keep in mind when developing SPMD programs is the clarity of abstraction, that is, how easy it is to understand the algorithm from reading the program's source code Depending on how the data is handled, this can range from awful to good If complex index algebra on the UE identifier is needed to determine the data relevant to a UE or the instruction branch, the algorithm can be almost impossible to follow from the source code (The Distributed Array pattern discusses useful techniques for arrays) In some cases, a replicated data algorithm combined with simple loop splitting is the best option because it leads to a clear abstraction of the parallel algorithm within the source code and an algorithm with a high degree of sequential equivalence Unfortunately, this simple approach might not scale well, and more complex solutions might be needed Indeed, SPMD algorithms can be highly scalable, and algorithms requiring complex coordination between UEs and scaling out to several thousand UEs [PH95] have been written using this pattern These highly scalable algorithms are usually extremely complicated as they distribute the data across the nodes (that is, no simplifying replicated data techniques), and they generally include complex load balancing logic These algorithms, unfortunately, bear little resemblance to their serial counterparts, reflecting a common criticism of the SPMD pattern An important advantage of the SPMD pattern is that overheads associated with startup and termination are segregated at the beginning and end of the program, not inside time critical loops This contributes to efficient programs and results in the efficiency issues being driven by the communication overhead, the capability to balance the computational load among the UEs, and the amount of concurrency available in the algorithm itself SPMD programs are closely aligned with programming environments based on message passing For example, most MPI or PVM programs use the SPMD pattern Note, however, that it is possible to use the SPMD pattern with OpenMP [CPP01] With regard to the hardware, the SPMD pattern does not assume anything concerning the address space within which the tasks execute As long as each UE can run its own instruction stream operating on its own data (that is, the computer can be classified as MIMD), the SPMD structure is satisfied This generality of SPMD programs is one of the strengths of this pattern Examples The issues raised by application of the SPMD pattern are best discussed using three specific examples:.

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try { // Bind to port 80, to provide a TCP service (like HTTP) ServerSocket myServer = new ServerSocket ( 80 ); // } catch (IOException ioe) { Systemerrprintln ("I/O error " + ioe); }

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