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Algorithm 10 displays the procedure for this processor choice and the subsequent scheduling of the free node n on Pmin This procedure is an implementation of lines 5 and 6 of the simple list scheduling (Algorithm 9) Algorithm 10 Start ime Minimization: Schedule Free Node n on Earliest-StartTime Processor Require: n is a free node tmin ; Pmin NULL for each P P do if tmin > max{tdr (n, P), tf (P)} then tmin max{tdr (n, P), tf (P)}; Pmin P end if end for ts (n) tmin ; proc(n) Pmin In the literature, list scheduling usually implies the above start time minimization method Many algorithms have been proposed for this kind of list scheduling (Adam et al [2], Coffman and Graham [38], Graham [80], Hu [93], Kasahara and Nartia [102], Lee et al [117], Liu et al [128], Wu and Gajski [207], Yang and Gerasoulis [210]) Some of these publications, especially the earlier ones, are based on restricted scheduling problems as discussed in Section 64 An Example To illustrate, simple list scheduling with start time minimization is applied to the sample task graph (eg, in Figure 41) and three processors Suppose the rst part of list scheduling established the node order a, b, c, d, e, f , g, i, h, j, k Figure 51 visualizes the scheduling process described in the following. Encoding Bar Code In .NET Using Barcode encoder for Visual .Related: .NET EAN-8 Generating , Generate UPC-E .NET , Create ISBN .NET

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If this presents a problem to the reader, and/or if the comment above convinces the reader that a uni ed motion planning algorithm may be f a limited value, the reader can skip the rest of this section. A reachable con guration is called a free con guration (FC); the subspace that contains all free con gurations is called the free con guration pace, FCS. Points in CS represent robot con gurations. A path in CS represents continuous. Generate PDF417 In Visual C# Using Barcode encoder for VS .Related: Print Intelligent Mail .NET

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Cluster of workstations, 11, 37, 195 Clustering, 119 141 algorithms, 121 124 contention model, 220, 221 de nition, 120 dynamic sequence, 137 138 initial, 121 linear, 124 128 algorithm, 127 128 ound, 125 contention model, 221 de nition, 124 example, 128 list scheduling, 135 138 contention model, 221 node duplication, 138 139 nonlinear, 124 performance, 141 principle, 121 122 scheduling on processors, 141 single edge, 128 135 contention model, 221 example, 131 to scheduling, 139 141 Code generation, 267 Common buffer, 230 Communication, 32, 49 concurrent, 76, 87, 188, 209 con ict, 19 contention, see Contention cost, 50, 68, 77, 163, 247 de nition, 50 function, 77 network model, 203 cost free, 76, 81, 87 delay, 75, 77, 247 248 device, 231 distance, 57 high, 105 interiteration, 33, 56, 64 65 interprocessor, 29, 76 intraiteration, 33, 56, 64 65 intraprocessor, 76 layer, 232, 245 local, 76 low, 105 medium, 105 network, see Network nonuniform, 58 overhead, 28 packet based, 235 port, 189 processor, 191.

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Cluster of workstations, 11, 37, 195 Clustering, 119 141 algorithms, 121 124 contention model, 220, 221 de nition, 120 dynamic sequence, 137 138 initial, 121 linear, 124 128 algorithm, 127 128 bound, 125 contention model, 221 de nition, 124 example, 128 list scheduling, 135 138 contention model, 221 node duplication, 138 139 nonlinear, 124 performance, 141 principle, 121 122 scheduling on processors, 141 single edge, 128 135 contention model, 221 example, 131 to scheduling, 139 141 Code generation, 267 Common buffer, 230 Communication, 32, 49 concurrent, 76, 87, 188, 209 con ict, 19 contention, see Contention cost, 50, 68, 77, 163, 247 de nition, 50 function, 77 network model, 203 cost free, 76, 81 87 delay, 75, 77, 247 248 device, 231 distance, 57 high, 105 interiteration, 33, 56, 64 65 interprocessor, 29, 76 intraiteration, 33, 56, 64 65 intraprocessor, 76 layer, 232, 245 local, 76 low, 105 medium, 105 network, see Network nonuniform, 58 overhead, 28 packet based, 235 port, 189 processor, 191.

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barcode library for .net generate, create bar code . in .net use .net framework barcode generation toinsert .The simulation of random distribution of particles using sequential addition method is different from the Metropolis technique in that he realizations of discrete random media are constructed by depositing spheres one by one into the box subject to the same condition of no overlap with all other particles. Thus, in the sequential addition method the particles do not move, and there is no shuffling of particles. The procedures adopted are as follows.Related: .NET Codabar Generating , Generate ITF-14 .NET , Create Interleaved 2 of 5 .NET

Algorithm 12 Create Node List 1: Assign a priority o each n V 2: Put source nodes n V : pred(n) = into priority queue Q 3: while Q = do Q only contains free nodes 4: Let n be the node of Q with highest priority; remove n from Q 5: Append n to list L 6: Put {ni succ(n) : pred(ni ) L} into Q 7: end while which costs O(log V) and the determination of the free nodes amortizes to O(E) Removing the node with the highest priority from the heap is O(1) An example for a metric that is not compatible with the precedence order is tl + bl a metric that gives preference to the nodes of the critical path Table 51 displays several node orders of the sample task graph obtained with node level based priority metrics The values of the node levels are given in Table 41 As analyzed in Section 44, calculating these levels has a complexity of O(V + E) For all these metrics the rst part of the simple list scheduling is thus O(V log V + E) (calculating levels: O(V + E) + sorting: O(V log V) or O(V log V + E)) Already the few examples in Table 51 illustrate the large variety of possible node orders In experiments, the relevance of the node order for the schedule length was demonstrated (eg, Adam et al [2], Sinnen and Sousa [177]) Unfortunately, most comparisons of scheduling algorithms (eg, Ahmad et al [6], Gerasoulis and Yang [76], Khan et al [103], Kwok and Ahmad [111], McCreary et al [136]) analyze entire algorithms: that is, the algorithms differ not only in one but many aspects This generally impedes one from drawing conclusions on discrete aspects of the algorithms (eg, on the node order) Still, most algorithms apply orders based on node levels and the bottom level order exhibits good average performance (eg, Adam et al [2], Sinnen and Sousa [177]) Breaking Ties Table 51 also shows examples where the node order is not fully de ned, indicated in the table by parentheses around the respective nodes Incidentally,.

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