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The key to parallel computing is exploitable concurrency Concurrency exists in a computational problem when the problem can be decomposed into subproblems that can safely execute at the same time To be of any use, however, it must be possible to structure the code to expose and later exploit the concurrency and permit the subproblems to actually run concurrently; that is, the concurrency must be exploitable Most large computational problems contain exploitable concurrency A programmer works with exploitable concurrency by creating a parallel algorithm and implementing the algorithm using a parallel programming environment When the resulting parallel program is run on a system with multiple processors, the amount of time we have to wait for the results of the computation is reduced In addition, multiple processors may allow larger problems to be solved than could be done on a single processor system As a simple example, suppose part of a computation involves computing the summation of a large set of values If multiple processors are available, instead of adding the values together sequentially, the set can be partitioned and the summations of the subsets computed simultaneously, each on a different processor The partial sums are then combined to get the final answer Thus, using multiple processors to compute in parallel may allow us to obtain a solution sooner Also, if each processor has its own memory, partitioning the data between the processors may allow larger problems to be handled than could be handled on a single processor This simple example shows the essence of parallel computing The goal is to use multiple processors to solve problems in less time and/or to solve bigger problems than would be possible on a single processor The programmer's task is to identify the concurrency in the problem, structure the algorithm so that this concurrency can be exploited, and then implement the solution using a suitable programming environment The final step is to solve the problem by executing the code on a parallel system Parallel programming presents unique challenges Often, the concurrent tasks making up the problem include dependencies that must be identified and correctly managed The order in which the tasks execute may change the answers of the computations in nondeterministic ways For example, in the parallel summation described earlier, a partial sum cannot be combined with others until its own computation has completed The algorithm imposes a partial order on the tasks (that is, they must complete before the sums can be combined) More subtly, the numerical value of the summations may change slightly depending on the order of the operations within the sums because floating point.

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The previous example familiarized you with the InetAddress class Below is a more complex example, which resolves hostnames to IP addresses and then attempts to perform a reverse lookup of the IP address Code for NetworkResolverDemo

AWSError error = egetErrors()get(0); String code = errorgetCode(); String message = errorgetMessage(); Systemerrprintf("select failed: %s: %s", code, message); } private void printSelectResults(QueryWithAttributesResult result) { for (String itemName : resultgetItems()keySet()) { Systemoutprintln(itemName); for (ItemAttribute attr : resultgetItems()get(itemName)) { Systemoutprintln("\t" + attrgetValue()); } } }

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import javanet*; // 3, Listing 2 public class NetworkResolverDemo { public static void main(String args[]) { if (argslength != 1) { Systemerrprintln ("Syntax NetworkResolverDemo host"); Systemexit(0); } Systemoutprintln ("Resolving " + args[0]); try { // Resolve host and get InetAddress InetAddress addr = InetAddressgetByName ( args[0] ); Systemoutprintln ("IP address : " + addrgetHostAddress() ); Systemoutprintln ("Hostname : " + addrgetHostName() ); } catch (UnknownHostException uhe) { Systemoutprintln ("Error - unable to resolve hostname" ); } } }

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arithmetic is nonassociative A good parallel programmer must take care to ensure that nondeterministic issues such as these do not affect the quality of the final answer Creating safe parallel programs can take considerable effort from the programmer Even when a parallel program is "correct", it may fail to deliver the anticipated performance improvement from exploiting concurrency Care must be taken to ensure that the overhead incurred by managing the concurrency does not overwhelm the program runtime Also, partitioning the work among the processors in a balanced way is often not as easy as the summation example suggests The effectiveness of a parallel algorithm depends on how well it maps onto the underlying parallel computer, so a parallel algorithm could be very effective on one parallel architecture and a disaster on another We will revisit these issues and provide a more quantitative view of parallel computation in the next chapter

The sample code defines the SelectExpression, makes the call to Select, and prints the results all in the same lineThe null parameter after SelectExpression in the call to selectItems() is the only other valid Select parameter: NextToken It is null here since this is an initial queryThe printSelectResults() method iterates through the map keys, which are returned by TypicaThis map is in the same format that batchPutAttributes() required in the previous Java snippet Each key is an ItemName and maps to an ItemAttribute listThe map could be empty if no items matched the SelectExpression query The prior example used a simple queryThe following example shows how to fetch multiple pages of select results using NextToken and uses a much more specific query:

How NetworkResolverDemoWorks In the previous example, we used a static method of InetAddress to return the local address Most commonly, however, we will be working with other systems on the network, so we need to learn how to use InetAddress to resolve their hostnames and obtain an IP address In this example, we use the static method, InetAddressgetByName() to return an InetAddress instance We then display the IP address and hostname, using the same methods in LocalHostDemo Running NetworkResolverDemo This application requires as a parameter either a hostname or an IP address To run, type:

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12 Oct 2018 ... In this article, we are going to learn how to generate PDF file using C# .

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how to write pdf file in asp.net c#

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how to write pdf file in asp.net c#

how to write pdf file in asp.net c#

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how to write pdf file in asp.net c#

how to write pdf file in asp.net c#

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