### Table 5: The simulation results for the perfect information, static and dynamic models.

"... In PAGE 15: ... The parameters we use in our experiments are the same as in Table 3 except the parameter S is not required and N = 1000. Table5 shows the simulation results. The second column gives a point estimate of the optimal value of the perfect information model over N trials.... ..."

### Table 2: Simulated and optimal execution times for selected Perfect Benchmarks programs

1992

"... In PAGE 13: ... In this experiment, we used the programs to illustrate our approach in evaluating the e ectiveness of a parallelizing compiler. Table2 lists the sequential execution times on the ideal machine of the selected Perfect Benchmarks programs. Also included in the table are the optimal parallel execution times at both the operation-level and the loop-level as well as the execution time on the ideal machine of the program after it is transformed by KAP.... ..."

Cited by 15

### Table 1: Summary of subprocedure MHevolve for perfect Metropolis-Hastings simulation of a locally stable point process.

1999

"... In PAGE 23: ... Note that, by construction, (iv) implies (i). Then min n (t; i) (the death candidate in Ln at time (t; i)) follows the same conditional distribution as MHdeath(Ln=2(t; i ? 1) \ Cj; Ln(t; i ? 1) \ Cj; min n=2(t; i); max n (t; i)) The nal form of MHevolve is as given in Table1 . Notice that, as was made plain in Theorem 3.... ..."

Cited by 25

### Table 1. Functional Unit Latencies In the simulations, we assumed perfect branch pre- diction, perfect instruction fetch bandwidth and per-

1998

Cited by 21

### Table 1. Functional Unit Latencies In the simulations, we assumed perfect branch pre- diction, perfect instruction fetch bandwidth and per-

1998

Cited by 21

### Table 5: Upscaling and base case parameter value for production characteristics. The latter entry indicates no modeling error, i.e. the uid ow simulator is perfect.

1998

"... In PAGE 16: ... to, i.e. no modeling error is assumed. See Table5 for production characteristics. 3.... ..."

Cited by 2

### Table 1 Recommended Simulation Parameters for Perfect Crystal -SiC Thermal Conductivity Calculation T (K) Steps Timestep (fs) Runs EF 1(ps) EF 2(ps)

### Table 2: Mean coalescence times in seconds for perfect Metropolis-Hastings simulation of a Strauss process using mh-cftp with varying cell-width z and a 10 10 window. Note np is held constant at 100.

1999

"... In PAGE 25: ... A typical invocation of the program implementing the Metropolis-Hastings algorithm to generate a Poisson point process might be mh-cftp -i quot;poisson quot; -n m2 -m m -z z -p p -s s ; which would produce a point pattern over a square region S divided into n = m2 square cells of side-length z, using random number seed s, the mean number of points in S being np. Table2 shows mean times (in seconds, measured on a Sun UltraSparc) taken to attain perfect simulation using various seeds, working with various invocations of mh-cftp using a Strauss process with density proportional to sr(x) with reference to the Poisson process considered above. Here r = 1:5 is the interaction radius, = 0:5 is the interaction parameter, and sr(x) denotes the number of pairs of points in x which are closer to each other than the interaction radius.... In PAGE 25: ...nteraction radius. Note that Eqs. (2.1,5.8) hold with K = p=z2. As can be seen in Table2 , there is weak evidence that e ciency is maximized for p in the region of 0:4. However it should be noted that standard deviations based on 30 replicates were of the order of 0:3.... ..."

Cited by 25

### Table 1: Homing failure rates for various correspondence methods. Homing failure is indicated by the percentage of simulation trials that produced a non-perfect catchment area, for various numbers of landmarks.

1999

Cited by 7