### Table 1: Constraints for place restructuring. ular integration of multiple constraints for diktiometry restructuring.

1992

"... In PAGE 6: ... We deal below with two restructurers, one for splitting to deal with polytopy, and one for merging to deal with monotopy. To a great extent these two are inverses, and we apply similar methods for both, as summarized in Table1 . We divide the constraints applied into three categories: geometric constraints on the positions of places, local path constraints about lo- cal functional relationships in the path graph, and non- local path constraints applied to larger portions of the path graph.... ..."

Cited by 9

### Table 12 Final fetch vector alphameric assignment scheme- values generated using mixed-integer linear programming.

"... In PAGE 13: ... The alphameric assignment scheme is shown in Table 12. Determination of fetch width constraints If the garbled word data were transformed into a magni- tude value using the alphameric assignment scheme shown in Table12 , it could be assumed that the garbled and correct forms of the same word would map into fair- ly similar (close) magnitude values. If the correct form W.... ..."

### Table 1: Symmetric Integer Programs

2007

"... In PAGE 8: ... 5 Computational Experiments In this section, we give empirical evidence of the effectiveness of orbital branching, we investigate the im- pact of choosing the orbit on which branching is based, and we demonstrate the positive effect of orbital fixing. The computations are based on the instances whose characteristics are given in Table1 . The in- stances beginning with cod are used to compute maximum cardinality binary error correcting codes [8], the instances whose names begin with cov are covering designs [15], the instance f5 is the football pool problem on five matches [6], and the instances sts are the well-known Steiner-triple systems [5].... In PAGE 9: ...1. Using branching rule 5, each instance in Table1 was run both with and without orbital fixing. Figure 2 shows a performance profile comparing the results in the two cases.... ..."

Cited by 2

### TABLE II TABLE FOR THE DYNAMIC PROGRAM (APPROXIMATION SCHEME)

2000

Cited by 9

### Table 1: Machine parameters (split into the integer datapathand the FP datapath if not common)

"... In PAGE 5: ... We extended the simulator to include register renaming through a physical register file and the issue mechanisms described in Section 2 and Section 3. See Table1 for the main architectural parameters of the machine. We used the programs from the Spec95 suite with their reference inputs to conduct our evaluation.... ..."

### Table 1: Machine parameters (split into the integer datapathand the FP datapath if not common)

"... In PAGE 5: ... We extended the simulator to include register renaming through a physical register file and the issue mechanisms described in Section 2 and Section 3. See Table1 for the main architectural parameters of the machine. We used the programs from the Spec95 suite with their reference inputs to conduct our evaluation.... ..."

### Table III. Prediction accuracy and coverage for integer programs Data Avg. reuses Avg. dist. Accuracy Accuracy Cover-

### Table 1: The size of the formulated 0-1 integer programming problem. # of nodes # of variables # of inequality constraints

"... In PAGE 8: ... (Note that each variable corresponds to a node group, while each inequality constraint corresponds to a partition of V .) Table1 shows the size of the 0-1 integer programming problem for networks of up to 12 nodes. The number of variables is the same as that of node groups, i.... In PAGE 13: ... In the case of Network 7, for example, the number of variables is 219 and that of inequalities is 1519. Comparing these values with Table1 , one can see that the number of variables is reduced by half and that of the inequality constraints is decreased by more than 90%. (Notice that Network 7 has nine nodes.... ..."

### Table 1: Computational complexities of the split-radix FFT and the integer versions (FxpFFT and IntFFT) when the coeffi- cients are quantized to Nc = 10 bits.

2000

"... In PAGE 4: ...and the numbers of real additions and shifts required in N-point FxpFFT and IntFFT. From Table1 , the numbers of additions of FxpFFT and IntFFT are approximately 100% and 50% more than that of the exact FFT, however, no real multiplication is needed. Comparing between FxpFFT and IntFFT, the number of additions of IntFFT is 29 - 37% less than FxpFFT while the number of shifts is 69 - 72% less.... ..."