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While all these existing coupling frameworks address the parallel data redistribution problem, they differ in the approaches they use to compute communication schedules, the data redistribution patterns that they support, and the abstractions they provide to the application layer Some of the existing systems gather distribution information from all the coupled models at each processor and then locally compute data redistribution schedules This implies a global synchronization across all the coupled systems, which can be expensive and limit scalability Furthermore, abstractions provided by most existing systems are based on message passing, which requires explicitly matching sends and receives and sometimes synchronous data transfers Moreover, expressing very general redistribution patterns using message passingtype abstractions can be quite cumbersome.



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Existing systems are brie y described below: InterComm [4]: InterComm is a framework that couples parallel components and enables ef cient communication in the presence of complex data distributions for multidimensional array data structures It provides the support for direct data transfer between different parallel programs InterComm supports parallel data redistribution in several steps: (1) locating the data to be transferred within the local memories of each program, (2) generating communication schedules (the patterns of interprocessor communication) for all processes, and (3) transferring the data using the schedules Note that these are three common steps in various data coupling frameworks But different frameworks may have different ways to compute communication schedules Furthermore, some have support for only limited data redistribution patterns InterComm supports data distributions with any complex patterns It uses a linearization space to nd the mapping between two parallel data objects.

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The Seine Coupe approach in addressing the parallel data redistribution problem has similarity to InterComm in that Seine Coupe also uses a linearization space to nd the mapping between data objects The differences between them include how the linearization is done, how the communication schedule is computed, and the abstractions they present to the application PAWS [3]: PAWS is a framework for coupling parallel applications within a component-like model It supports redistribution of scalar values and parallel.

Figure 5.17 Examples of the spectral leakage or two-tone characteristics for a 100 sample filter as the major signal frequency is varied from bin 10 to bin 11. The minor signal, 20 dB or 40 dB smaller, is in bin 16. [Source: Meikle, H.D., Modern Radar Systems, Artech House, Norwood, Massachusetts, 2001.]

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In this chapter, we ve looked at two elements of a PC that are generally overlooked and underestimated. Choosing a good, sturdy case and a PSU that can deliver enough power to the system makes all the difference to your system in the long run. Don t think of the case and PSU as unimportant components they are as vital to the PC as anything else you add. Plan ahead and think about possible future upgrades, and make sure the case and power supply you choose will be ready to meet the challenges that your PC will face in the future. Don t skimp on them, and get the best that you can afford. In the next chapter, you will be looking at motherboards and CPUs.

ome people believe that the PC case is just an enclosure for the PC s contents, and others believe that the case sets the stage for everything else inside Whether it s just the skin around the package or it makes the package be what it is, the case is undoubtedly a key component in an HTPC We are inclined to put a lot of weight behind and thought into the selection process for an HTPC case, particularly because looks, layout, and functionality matter more for such cases than they do for ordinary desktop PCs Our thinking is that the case must not only provide desirable technical characteristics and this chapter digs into them deeply, never fear but also that it must fit into a typical entertainment center both physically and visually Power supplies aren t thrown into this chapter randomly, just to give them a place to go.

Figure 6.4. (a) Quartic polynomial with (b) its first-order derivative, (c) second-order derivative, and (d) the corresponding Newton step. (Example 6.7)

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