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Double Loops Loop Nests The next logical step in dependence analysis of loops is to extend the described concepts to double and multiple nested loops Example 7 displays a double loop over the indices i and j, containing the two statements, or tasks, S and T in the kernel Example 7 Double Loop for i = 0 to 5 do for j = 0 to 5 do S: A(i+1,j) = B(i,j) + C(i,j) T: B(i+1,j+1) = A(i,j) + 1 end for end for Suitable for the double loop, the arrays used in the tasks are two dimensional, whereby the index variable i of the outer loop is used only in the subscripts of the arrays rst dimension and the index variable j only in the subscripts of the second dimension While this is common practice in nested loops, it is neither a guaranteed nor a necessary condition for the dependence analysis in nested loops The arrays, for example, might only have one dimension, and the subscripts might be functions of more than one index variable Relevant for a dependence relation is only the reference of two different tasks to the same array element What the index variable is to the single loop is now, in a straightforward generalization, an index vector of two dimensions An instance of the double loop kernel (ie, an iteration) is determined by the two corresponding values of the index variables i and j Also, an instance of one of the tasks S and T is denoted by S(i, j) and T(i, j), respectively The extension to a more general nest of loops follows a similar pattern every loop simply contributes one dimension to the index vector In the same way, the index variable of a single loop can be treated as an index vector of one dimension By examining he tasks of the loop in Example 7, it becomes apparent that instance S(i + 1, j + 1) depends on instance T(i, j), caused by the references to the elements of array B, and instance T(i + 1, j) depends on S(i, j), caused by the references to the elements of array A As a logical consequence of the generalization from the index variable to an index vector, the dependence distance is also expressed as a distance vector For the identi ed dependence relations in Example 7, the distance vectors are (1, 1), for S(i + 1, j + 1) depending on T(i, j), and (1, 0), for T(i + 1, j) depending on S(i, j) So there are two uniform dependences, as the distance vector is constant for every dependence The determination of the dependence relations and the distance vectors for the loops in Example 5 and Example 7 are relatively simple In real programs, however, various circumstances can make dependence analysis more complicated and time consuming Sometimes it might even be impossible to determine the dependence relation of a program: for example, when a subscript of an array, which is read and written in various tasks, is a function of an input variable of the program In that case, the dependence relations can only be established at runtime A conservative approach,.

QUALITY OF SERVICE PROVISIONING FOR LRD REAL-TIME TRAFFIC Code-39 Creation In VS NET Using Barcode maker for ASP Strong autocorrelations typically seen in video traf c make equivalent bandwidth omputations for heterogeneous cell-loss bounds intractable To address this, the framing strategy is combined with an active cell-discard mechanism with prioritized cell-dropping, the latter utilizing the history of dropped cells and target cell-loss bounds for each VC Upper bounds on the equivalent bandwidth needed to support a given workload with a target quality of service are developed These are validated through numerical and simulation results from variable bit rate MPEG-I video traces A high-level view of the proposed architecture is as follows 1 A Framing Structure on a Per-VC Basis To provide heterogeneous delay-jitter bounds, a framing structure is induced on VCs, similar to that in Golestani [9 11] (Differences between the two approaches are described later.

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in the sense that the discovered dependence structure includes all constraints of the true structure, is then to assume dependence between all respective tasks Loop Stride The dependence analysis presented so far is based on the assumption that the loop stride (ie, increment or decrement of the index variable per iteration) is 1 In order to handle different strides, as they happen to appear in real loops, the loop must be normalized to a stride of 1 at least during the analysis phase The normalization involves a transformation of all expressions where the original index variable is included (Banerjee et al [17]) DependenceTests The area of dependence analysis in loops mainly concentrates on array subscripts that are linear functions of the index variables But even with this restriction, the determination of a dependence can be quite time consuming, as exact solutions are based on integer programming This, together ith the fact that it is sometimes suf cient to know whether there is a dependence or not, led to the utilization of approximation methods It suggests that these approximation methods often do not determine the distance vector; at most, they compute a direction vector, which is the vector of the signs of the distance vector s components Some loop transformations only require knowledge of such a direction vector Many so-called dependence test algorithms have been proposed in the past; consult, for example, Banerjee et al [15, 16], Blume and Eigenmann [23], Eisenbeis and Sogno [58], Petersen and Padua [148], Pugh [155], Wolfe [202], and Yazici and Terziologu [212].

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) Consider a virtual circuit (VC), i, with a desired delay-jitter bound Mi The frame structure splits time for this VC into juxtaposed intervals of length Mi at each multiplexing point Cells from VC i that arrive in a given frame at a multiplexer are buffered, and not transmitted until the beginning of the next frame time If suf cient capacity is available to transmit these cells in the next interval, all cells arrive at the next hop within an interval of length Mi This way, they are guaranteed to meet a delay-jitter bound of Mi Also, if Hi is the number of hops for VC i, and Di is a bound on the one-way propagation and processing delay, all cells that make it to the receiver are guaranteed an end-to-end delay bound of Hi Mi Di 2 Priority Scheduling.

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