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3. Enter a descriptive name for your search, so you can choose it correctly from the pop-up menu when using Find. 4. Tab to the Regular Expression column and enter the expression, as shown in Figure 25-9. (If you copied it from the Find & Replace tab you can paste it now.) 5. Tab again and enter the replacement pattern. Leave it blank if no replacement exists (as in the example shown here). As soon as you click anywhere within the Preferences window or click OK to close the window, your new expression is set. Click OK to close the Preferences window and save it. The newly entered GREP is now available from the bottom part of the Find & Replace pop-up menu and appears with your name so you can reuse it. To remove an expression if it doesn t work as planned, select it from the list, and then click Delete.

only provides a better understanding of both aspects but also implicitly indicates that different partitioners can be potentially applied to address different application characteristics The SAMR application is used to illustrate the taxonomy in the discussion below In Table 11, applications are characterized based on their execution behavior, activity, granularity, and dependency The execution behavior can be computation intensive, communication intensive, or IO intensive [1, 2] For example, most SAMR applications are computation intensive, belonging to high-performance scienti c computing category Due to deep levels of adaptive re nements, SAMR applications can also be communication intensive In some cases, when dealing with large amounts of data, SAMR applications can fall into IO-intensive category Experiments show that during the entire course of execution, SAMR applications may run in different execution modes as the simulated physical phenomena evolve [1, 2] Application activities are classi ed as dynamic or static.

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You now have a general-purpose script. You can set the variables $x and $y to any two values you want, either at some other place in your code, or as a result of input from the user. Then, when you run the preceding line of code, the script outputs the sum of those two values. Re-run the script with different values for $x and $y, and you get a different result.

Many embarrassingly parallel applications belong to the static application category, for example, parallel geometrical transformations of images and Monte Carlo simulations [3] SAMR applications, on the other hand, are dynamic in nature because of their dynamic adaptivity The dynamic behavior of SAMR applications may demonstrate localized adaptivity pattern or scattered adaptivity pattern in different execution phases From the perspective of divisibility, some applications are ne grained [4], some are coarse grained [5], while others are not divisible at all [6, 7] Workloads in the divisible load scheduling class are assumed to be homogeneous and arbitrarily divisible in the sense that each portion of the load can be independently processed on any processor on the network Coarse-grained divisible applications typically involve dependencies among subtasks Indivisible tasks are atomic and cannot be further divided into smaller subtasks and have to be completely processed on a single processor.

This has a general solution of the form Tn (t) = An cos( n t) + Bn sin( n t) (12.27)

FIGURE 5.23 Geometry of a circularly polarized annular-ring microstrip antenna with a pair of inserted slits (design B). The microstrip feed line is at the inner boundary of the patch. (From Ref. 7, C 1999 IEEE, reprinted with permission.)

5. Press and hold the W key, or press the W key multiple times until the Position Locator indicates that you re in the narrow hallway. If necessary, let the screen redisplay the model. 6. Continue to walk to the end of the diagonal segment of hallway, as shown in the Position Locator. If necessary, drag slightly to the left or right to adjust your view. Don t mind that along the way, you may be seeing through walls. 7. Drag to the right to turn to the right, until the Position Locator shows the center target line horizontal, facing right. You should be able to see the table inside the bedroom, through a partially open door.

SAMR applications can fall into the ne-grained or coarse-grained divisible categories When the underlying physical domain being modeled exhibits more homogeneity, the load associated with this domain belongs to the ne-grained divisible category However, when the physical domain exhibits scattered heterogeneity with deep re nements, the load may be classi ed as coarse-grained divisible Note that SAMR applications involve iterative operations and frequent communications and obviously cannot be considered as embarrassingly parallel The last criterion in the table is dependency Independent applications are common in the divisible load scheduling category, such as parallel low-level image processing and distributed database query processing [4] Work ow.

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Reference:

Figure 6.6 Flow control levels in the 2G-SGSN applied to every LLC-PDU [12].

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