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Problem How can a problem's data be decomposed into units that can be operated on relatively independently Context The parallel algorithm designer must have a detailed understanding of the problem being solved In addition, the designer should identify the most computationally intensive parts of the problem, the key data structures required to solve the problem, and how data is used as the problem's solution unfolds After the basic problem is understood, the parallel algorithm designer should consider the tasks that make up the problem and the data decomposition implied by the tasks Both the task and data decompositions need to be addressed to create a parallel algorithm The question is not which decomposition to do The question is which one to start with A data based decomposition is a good starting point if the following is true

It is not an error to pass an ItemName that does not exist; neither is it an error to pass an AttributeName or AttributeValue that does not exist If there is no matching item, the call will return normally and nothing will happen If there is no match for an AttributeName or AttributeValue parameter, it will be ignored while other valid attributes in the request are deleted However, a single oversized parameter will trigger an InvalidParameterValue and no deletes in the request will be processed

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The registration details include the location of the registry, followed by an optional port and then the name of the service Using static methods of the class javarmiNaming, which is responsible for retrieving and placing remote object references in the registry, we register the service so that clients can access it The details, represented by our registration string, are passed to the Naming rebind() method, which accepts as a parameter a registration name and an instance of the javarmiRemote interface We pass the service created earlier, and the service becomes bound to the registry The binding process creates an entry in the registry for clients to locate a particular service, so that if the service is shut down, it should of course unbind itself If no errors occur, the service is then available for remote method invocation

Writing a client that uses an RMI service is easy compared with writing the service itself The client needs only to obtain an object reference to the remote interface, and doesn't need to be concerned with how messages are sent or received or the location of the service To find the service initially, a lookup in the RMI registry is made, and after that, the client can invoke methods of the service interface just as if it were a local object The next example demonstrates how to turn a remote lightbulb on and off

The most computationally intensive part of the problem is organized around the manipulation of a large data structure Similar operations are being applied t different parts of the data structure, in such a way that o the different parts can be operated on relatively independently

This Java code shows how to delete one specific attribute value from an existing item:

import javarmi*;

For example, many linear algebra problems update large matrices, applying a similar set of operations to each element of the matrix In these cases, it is straightforward to drive the parallel algorithm design by looking at how the matrix can be broken up into blocks that are updated concurrently The task definitions then follow from how the blocks are defined and mapped onto the processing elements of the parallel computer Forces The main forces influencing the design at this point are flexibility, efficiency, and simplicity

SimpleDB simpleDB = new SimpleDB(accessKeyID, secretAccessKey); try { Item oldItem = simpleDBgetDomain("users")getItem("1234567"); boolean replace = false; ItemAttribute delAttr = new ItemAttribute("tags", "App-Engine", replace); oldItemdeleteAttributes(CollectionssingletonList(delAttr)); Systemoutprintln("delete attributes succeeded"); } catch (SDBException e) { AWSError error = egetErrors()get(0); String code = errorgetCode(); String message = errorgetMessage(); Systemerrprintf("delete attributes failed: %s: %s", code, message); }

// 11, Listing 4 public class LightBulbClient { public static void main(String args[]) { Systemoutprintln ("Looking for light bulb service"); try { // Check to see String registry if (argslength { registry = } if a registry was specified = "localhost"; >=1) args[0];

Flexibility Flexibility will allow the design to be adapted to different implementation requirements For example, it is usually not a good idea to narrow the options to a single computer system or style of programming at this stage of the design Efficiency A parallel program is only useful if it scales efficiently with the size of the parallel computer (in terms of reduced runtime and/or memory utilization) Simplicity The decomposition needs to be complex enough to get the job done, but simple enough to let the program be debugged and maintained with reasonable effort

// Registration format //registry_hostname (optional):port /service String registration = "rmi://" + registry + "/RMILightBulb"; // Lookup the service in the registry, and obtain // a remote service Remote remoteService = Naminglookup ( registration ); // Cast to a RMILightBulb interface RMILightBulb bulbService = (RMILightBulb) remoteService; // Turn it on Systemoutprintln ("Invoking bulbserviceon()"); bulbServiceon(); // See if bulb has changed Systemoutprintln ("Bulb state : " + bulbServiceisOn() ); // Conserve power Systemoutprintln ("Invoking bulbserviceoff()"); bulbServiceoff(); // See if bulb has changed Systemoutprintln ("Bulb state : " + bulbServiceisOn() ); } catch (NotBoundException nbe) { Systemoutprintln ( "No light bulb service available in registry!"); } catch (RemoteException re) { Systemoutprintln ("RMI Error - " + re); } catch (Exception e) { Systemoutprintln ("Error - " + e); } } }

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