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Scalability How many processors can the parallel program effectively utilize The scalability of a program is restricted by three factors First, there is the amount of concurrency available in the algorithm If an algorithm only has ten concurrent tasks, then running with more than ten PEs will provide no benefit Second, the fraction of the runtime spent doing inherently serial work limits how many processors can be used This is described quantitatively by Amdahl's law as discussed in 2 Finally, the parallel overhead of the algorithm contributes to the serial fraction mentioned in Amdahl's law and limits scalability

someSocketsetSendBufferSize(4096);

To determine the size of the current send buffer, you can call the Socket getSend Buffer Size() method, which returns an int value

Efficiency How close does the program come to fully utilizing the resources of the parallel computer Recall the quantitative definition of efficiency given in 2: Equation 51

Since needed application data was completely unreachable for a longer than expected time period, we could not follow the usual procedure of serving of App Engine applications from an alternate data center, because doing so would have resulted in inconsistent or unavailable data for applications

// Get the default size int size = someSocketgetSendBufferSize();

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P is the number of PEs, T(1) is some sequential reference time, and T(P) is the parallel time with P PEs S(P) is the speedup The most rigorous definition of efficiency sets T(1) to the execution time of the best sequential algorithm corresponding to the parallel algorithm under study When analyzing parallel programs, "best" sequential algorithms are not always available, and it is common to use the runtime for the parallel program on a single PE as the reference time This can inflate the efficiency because managing the parallel computation always incurs some overhead, even

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Changing buffer size will be more effective with the DatagramSocket class When buffering writes, the preferable choice is to use a BufferedOutputStream or a BufferedWriter 6444 SO_LINGER Socket Option When a TCP socket connection is closed, it is possible that data may be queued for delivery and not yet sent (particularly if an IP datagram becomes lost in transit and must be resent) The linger socket option controls the amount of time during which unsent data may be sent, after which it is discarded completely It is possible to enable/disable the linger option entirely, or to modify the duration of a linger, by using the SocketsetSoLinger(boolean onFlag, int duration) method:

when executing on a single PE Efficiency is closely related to scalability because every highly scalable algorithm is also highly efficient Even when the scalability is limited by the available number of tasks or the parallel hardware, however, algorithms can differ in their efficiency

// Enable linger, for fifty seconds someSocketsetSoLinger( true, 50 );

This is a key insight into the different levels of availabilityThe root cause of the problem was a software bug, but that s not the whole storyThe interesting part is that there was a choice to be made Google engineers had a 30-minute-old copy of all the data for the thousands of AppEngine appsThey could have just switched it on at a different data center However, the choice was essentially made for them because they had a consistency guarantee to uphold Some data would be missing, some would be stale, and in the end, they would have no way to reconcile the divergent updates to stale data With SimpleDB, that same choice has already been made, but the difference is that availability is chosen over consistency It has already been decided, and the mechanism is already in place to synchronize up the stale or temporarily missing data The important thing to realize is that outages inevitably occur, even at Google and Amazon, and this leaves a choice for the developers who use these services If an outage causes the temporary loss of 30 minutes worth of data, is it better for your app to continue running without that data and have it synced up later or is it better for the app to wait out a six-hour outage unavailable to all users, even those unaffected by the data issue SimpleDB is a solution for those applications that would benefit from continuing to offer users access to the system even if the data is stale for a while If all the data in the application belongs to the user for example, in an email application the user is probably going to argue for the ability to keep working even if the data entered between 6:00 am and 6:30 am is absent for a whileWhen the application provides quantifiable business value, the decision can be far easier to makeWhen you weigh the cost of your entire online shopping cart application going down for all users for six hours in the middle of the day, against the cost of serving 30-minute-old stale shopping cart data to only those users who were active between 6:00 am and 6:30 am, there might be a dollar value difference you can compare.

Maintainability Is the program easy to debug, verify, and modify Casting an algorithm into source code is almost never a one time proposition Programs need to be debugged, new features added, performance tuned, etc These changes to the source code are referred to as maintenance Programs are more or less maintainable depending on how hard it is to make these changes and to do them correctly

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