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Initialize The program is loaded onto each UE and opens with bookkeeping operations to establish a common context The details of this procedure are tied to the parallel programming environment and typically involve establishing communication channels with other UEs Obtain a unique identifier Near the top of the program, an identifier is set that is unique to each UE This is usually the UE's rank within the MPI group (that is, a number in the interval from 0 to N 1, where N is the number of UEs) or the thread ID in OpenMP This unique identifier allows different UEs to make different decisions during program execution Run the same program on each UE, using the unique ID to differentiate behavior on different UEs The same program runs on each UE Differences in the instructions executed by different UEs are usually driven by the identifier (They could also depend on the UE's data) There are many ways to specify that different UEs take different paths through the source code The most common are (1) branching statements to give specific blocks of code to different UEs and (2) using the UE identifier in loop index calculations to split loop iterations among the UEs Distribute data The data operated on by each UE is specialized to that UE by one of two techniques: (1) decomposing global data into chunks and storing them in the local memory of each UE, and later, if required, recombining them into the globally relevant results or (2) sharing or replicating the program's major data structures and using the UE identifier to associate subsets of the data with particular UEs Finalize The program closes by cleaning up the shared context and shutting down the

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A special type of socket, the server socket, is used to provide TCP services Client sockets bind to any free port on the local machine, and connect to a specific server port and host The difference with server sockets is that they bind to a specific port on the local machine, so that remote clients may locate a service Client socket connections will connect to only one machine, whereas server sockets are capable of fulfilling the requests of multiple clients The way it works is simple clients are aware of a service running on a particular port (usually the port number is well known, and used for particular protocols, but servers may run on nonstandard port numbers as well) They establish a connection, and within the server, the connection is accepted Multiple connections can be accepted at the same time, or a server may choose to accept only one connection at any given moment Once accepted, the connection is represented as a normal socket, in the form of a Socket object once you have mastered the

The first thing to understand is that even though the SimpleDB consistency guarantee is relaxed compared to relational databases, there is still atomicity and durabilityThe unit of atomicity is the itemWhen you update the attributes of an item via a single PutAttributes request, the entire update is applied atomically It may take some time before the update is fully visible to clients attempting to retrieve that item via a call to GetAttributes or SelectThis is the same type of delay you might see with a masterslave relational database cluster, where the slave database services queries, even though it is always slightly out of sync with the master that accepts all the writesThe time it takes to replicate in SimpleDB is called the consistency window Regardless of the consistency window, SimpleDB always presents an internally consistent view of the itemThe item will have the prior state of the attributes or the new state of the attributes; it will never have a mixed state, where some of the new attribute values have been applied and some have notThis is atomicity at the item level At a higher level of granularity, this does not hold If you issue a batch put and update two items at once, subsequent reads of that data could result in one of the items being updated but not the other But, again, within each item, partial updates will never be shown Given how lean the SimpleDB API is, BatchPutAttributes is the only higher level of granularityThere are no transactions and so no opportunity for dirty reads or any isolation levels It could be said that if an application requires transactions, SimpleDB will not be the right choice of database, and this might be true But if the real application requirement is for atomicity rather than strictly transactions, placing all the necessary data inside one item can accomplish thatThis can serve as a workaround for the lack of transactions: Place the data that must change atomically within a single item and update it using a single call to PutAttributes using a conditional write In SimpleDB, PutAttributes can be used for all three of initial inserts, updates, and deleting or clearing of values.

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