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SimpleDB simpleDB = new SimpleDB(accessKeyID, secretAccessKey); boolean replace = false; ItemAttribute[] userData = new ItemAttribute[] { new ItemAttribute("userid", "Mocky", replace), new ItemAttribute("location", "Oswego", replace), new ItemAttribute("tags", "SimpleDB", replace), new ItemAttribute("tags", "Azure-Table", replace), new ItemAttribute("tags", "App-Engine", replace), }; try { Domain domain = simpleDBgetDomain("users"); Item newItem = domaingetItem("1234567"); newItemputAttributes(ArraysasList(userData)); Systemoutprintln("put attributes succeeded"); } catch (SDBException e) {

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Join See [fork/join] JVM See [Java Virtual Machine] Latency The fixed cost of servicing a request, such as sending a message or accessing information from a disk In parallel computing, the term most often is used to refer to the time it takes to send an empty message over the communication medium, from the time the send routine is called to the time the empty message is received by the recipient Programs that generate large numbers of small messages are sensitive to the latency and are called latency bound programs

While sending messages is useful, it is only part of the functionality of the JavaMail API Reading messages from an Internet mail server (such as an IMAP/POP3 account or a newsgroup), is also possible, as the next example demonstrates Code for ReadMailDemo

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import javaxmail*; import javaxmailinternet*; // 13, Listing 3 public class ReadMailDemo { public static void main (String args[]) { int argc = argslength; // Check for valid number of parameters if (argc != 4) { Systemoutprintln ("Syntax :"); Systemoutprintln ( "java ReadMailDemo protocol host username password"); return; }

Lazy evaluation A scheduling policy that does not evaluate an expression (or invoke a procedure) until the results of the evaluation are needed Lazy evaluation may avoid some unnecessary work and in some situations may allow a computation to terminate that otherwise would not Lazy evaluation is often used in functional and logic programming

AWSError error = egetErrors()get(0); String code = errorgetCode(); String message = errorgetMessage(); Systemerrprintf("put attributes failed: %s: %s", code, message); }

String String String String try {

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Linda A coordination language for parallel programming See also [tuple space] Load balance In a parallel computation, tasks are assigned to UEs, which are then mapped onto PEs for execution The net work carried out by the collection of PEs is the "load" associated with the computation Load balance refers to how that load is distributed among the PEs In an efficient parallel program, the load is balanced so each PE spends about the same amount of time on the computation In other words, in a program with good load balance, each PE finishes with its share of the load at about the same time

Instances of the ItemAttribute class are used to the name/value pairs, each with a replace flag In this example, the attributes are stored in an array and subsequently converted to a List for the putAttributes() call, where the actual web service call is made Notice that the sample code stores the multi-valued attribute tags by creating a separate ItemAttribute for each valueAlso notice that the putAttributes() method is in the Item class and not in the SimpleDB class

= = = =

The process of distributing work to UEs such that each UE involved in a parallel computation takes approximately the same amount of time There are two major forms of load balancing In static load balancing, the distribution of work is determined before the computation starts In dynamic load balancing, the load is modified as the computation proceeds (that is, during runtime)

args[0]; args[1]; args[2]; args[3];

PutAttributes Snippet in C#

Locality The extent to which the computations carried out by a PE use data that is associated with (that is, is close to) that PE For example, in many dense linear algebra problems, the key to high performance is to decompose matrices into blocks and then structure the calculations in terms of these blocks so data brought into a processor's cache is used many times This is an example of an algorithm transformation that increases locality in a computation

// Get a session, with default system properties Session mySession = SessiongetDefaultInstance (SystemgetProperties(), null); // Get a specific mail store, such as // imap/pop3/news Store myStore = mySessiongetStore(protocol); myStoreconnect (host, username, password); // Request the INBOX folder for this mail store Folder myFolder = myStoregetFolder("INBOX"); if (myFolder == null) { Systemerrprintln ("No default folder available"); return; } Systemoutprintln ("Accessing " + myFoldergetFullName() + " folder"); // Open in READ_ONLY mode myFolderopen(FolderREAD_ONLY); int messagecount = myFoldergetMessageCount(); Systemoutprintln (myFoldergetFullName() + " has " + messagecount + " messages"); Message[] message = myFoldergetMessages (); for (int i = 0; i < messagelength; i++) { Address[] fromAddr = message[i]getFrom(); Systemoutprintln (fromAddr[0] + ":" + message[i]getSubject()); } myFolderclose(false); } catch (MessagingException me) { Systemerrprintln ("Messaging failure : " + me); } catch (Exception ex) { Systemerrprintln ("Failure : " + ex); } } }

To accomplish PutAttributes in C#, use this code:

Massively parallel processor (MPP) A distributed memory parallel computer designed to scale to hundreds if not thousands of processors To better support high scalability, the computer elements or nodes in the MPP machine are custom designed for use in a scalable computer This typically includes tight integration between the computing elements and the scalable network

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