### Table 3: Computational results with LOP Even if the solution of the LP-relaxation is found in reasonable time, the solution of the MIP remains di cult. Due to the large number of fractional variables fl in the optimal 7

### Table 1: Run times for Compute-ordered-

1996

"... In PAGE 7: ... The run times reported are milliseconds of CPU time usage. Run times for Compute-ordered-messages are shown in Table1 . The algorithm is implemented on top of IDEAL, a software package for Bayesian net- work inference [Srinivas and Breese, 1990].... ..."

Cited by 3

### Table 8: Relative Run Times in the Computational Testing Opns. Run Times Number

1991

"... In PAGE 30: ...A major advantage of the CNC algorithm is seen in Table8 which shows the average run times of the three approaches. It is clear that the CNC algorithm is several orders of magnitude faster than a simulation.... ..."

Cited by 1

### Table 1. Graph information and running time [sec.]. Runtime columns show total running times for computing a layout.

2007

"... In PAGE 6: ... The fe * graphs are un- structured meshes related to uid dynamics, structural mechanics, or combinatorial optimization problems. Figures 7 - 11 show some of the layouts computed by our algorithm, whereas Table1 gives infor- mation about the graphs. Each image is accompanied with a layout Fig.... In PAGE 7: ... Our algorithm was implemented in C++, Cg, and OpenGL. Table1 shows the running time of our algorithm when using only the CPU and using the GPU to accelerate the computation. It also shows the running times for the FM3 algorithm, produced on a 2.... ..."

Cited by 2

### Table 1: Sensitivity computation run time.

1996

"... In PAGE 3: ... The number of sensitivi- ties required was unusually large in this example, which was chosen to showcase the efficiency of gradient computation. The run times of SPECS with both the adjoint and direct method on this benchmark circuit are shown in Table1 . From the table, we see that the total run time for a JiffyTune iteration would be 24.... ..."

Cited by 8

### Table 3: Running time to compute Renamed-4-Horn-LUB in CPU sec. Averaged over 50 runs.

Cited by 2

### Table 1: Run-time for MCM computation for the 6 largest ISCAS 89/93 benchmarks.

"... In PAGE 3: ... This approach is attributed to Lawler [10]. Table1 shows the run-times of the algorithms on some of the ISCAS 89/93 benchmark circuits. In the table, a118 a6a119a118 is the num- ber of vertices in the graph, a118 a10a119a118 is the number of edges, and a118 a120a121a118 is the number of delay elements.... ..."

### Table 1: Run-time for MCM computation for the 6 largest ISCAS 89/93 benchmarks.

"... In PAGE 3: ... This approach is attributed to Lawler [10]. Table1 shows the run-times of the algorithms on some of the ISCAS 89/93 benchmark circuits. In the table, a118 a6a119a118 is the num- ber of vertices in the graph, a118 a10a119a118 is the number of edges, and a118 a120a121a118 is the number of delay elements.... ..."

### Table 3. The running time varying with the number of computing nodes

"... In PAGE 10: ... First we ran the original program (all pixels are processed with the simplex algorithm) on an increasing number of processors to determine how the running time and computing speed (reciprocal of running time) of the program vary with the number of processors. From Table3 we can see that, as expected, there is an approximately linear speedup with the number of processors. Since there is no interprocessor communication or search, the speedup will be approximately linear regardless of the number of processors.... ..."