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Figure 4.20 illustrates how to compute the delay bound in 4.26.. As shown in Figure 4.20 a., the maximum delay of the packet in consideration tagged packet. at node 1, d1 , is irri q Lmax rr. At node k, k s 2, 3, . . . , K, we have d k s L irri q Lmax rr, as shown in Figure 4.20 b.. Therefore, we have Di s d1 q K y 1. d k , which gives us the bound in 4.26.. Intuitively, 4.26. means that, although the session actually traverses a series of schedulers, it behaves as if it were served by a single scheduler with rate ri , so that when the source sends a burst of length i , it experiences a worst-case delay irri , which is the same as that in a GPS server. The second term models the situation at each scheduler where another packet from session i will receive its service before the tagged packet, so the tagged packet is delayed by at most L irri . The third term reflects the fact that if the tagged packet arrives at a busy scheduler, it may have to wait up to Lmax rr before it is served. The inequality 4.26. can easily be extended to allow for more general situations, such as heterogeneous link rates w18x.

partitioners may not be the method of choice and JOSTLE-D does little better in terms of migration than its multilevel counterpart JOSTLE-MD The same trends are in evidence with the VPI results as the edge weight ratio decreases from 10:1 to parity (thus putting increasing emphasis on minimizing migration), the migration certainly decreases, but at the cost of increasing cut-weight However, comparing the two, JOSTLE(VPI) does much better than the diffusive partitioners For example, with the ratio 10:1, JOSTLE(VPI) has almost identical cut-weight to JOSTLE-MD (284% against 283%) but considerably better migration (278% against 320%) and with the ratio 1:1, JOSTLE(VPI) even reduces migration down to 227% Perhaps most important, however, the VPI framework appears to offer much ner control over the migration/cut-weight trade-off At the bottom of the tables, we also present averages for two other avors of the VPI scheme.

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Johnson Carter s solution to some of the hide-and-seek games was to initiate surprise inspections. Bernie s feeling was that if the factory were hiding any quality problems, inspections at unexpected times would make them easier to nd. Bernie announced that, as a representative of his company, I would now be making random visits. No advance warning of my arrival would be given, and the factory was to ensure that its doors were open at all times. It seemed demanding and a bit presumptuous, and I thought that the factory might protest the move as insulting. Quite the opposite, Sister seemed surprised that it had taken so long for us to become so vigilant. Bernie took an unusual approach to such inspections. He would randomly announce to factory reps that I would visit on a particular day just to gauge their reaction. If the factory reps offered no protest about the visit, he would cancel the trip, guring that there must be nothing interesting to see. Alternatively, if anyone at the factory hinted that some days might be inconvenient, I was to rush to the factory during that time. During one of these suggested blackout periods, I ew into Shantou and arrived only to nd that our product was not in process, that we had almost no nished product in the warehouse to inspect, and that Sister was out of town on business. In other words, it was a wasted trip.

The row marked local uses local matching (and hence should produce very similar results to the MLDD scheme, as discussed in Section Discussion ) However, as suggested in Section Local Matching, it does seem that the local matching results in worse partition quality (293 348% against 284 347%) without improving the migration (280 232% against 278 227%) Finally, the row marked IML uses iterated multilevel re nement (Section 1724), repeatedly coarsening and uncoarsening to nd better results Although not a serious contender in a time-critical application such as the repartitioning of parallel adaptive meshes, it does indicate very well the exibility of the VPI framework.

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