### Table 1: CPU Times and algorithm efficiency in pruning dominated paths

"... In PAGE 4: ... All the CPU times are based on a SUN SPARC classic workstation. Table1 summarizes the inputs. Each of the three HLS benchmarks namely Differential equation, Ellip- tical filter and AR filter, have been processed with different initial control steps(ics).... In PAGE 5: ... 3). Table1 also gives details of the CPU time as well as the efficiency of the algo- rithm in pruning the dominated paths. The pruning is quite effective as the ratio of total paths (column 5) to non-dominated paths (column 8) is as high as 390.... ..."

### TABLE IV SPEED-UPS AND EFFICIENCIES OF STRIP DECOMPOSITION PARALLELIZATION ALGORITHM OF FAST DIRECT POISSON SOLVER FOR TEST GRID M1

in Strip Decomposition Parallelization of Fast Direct Poisson Solver on a 3D Cartesian Staggered Grid

### Table 20. CPU (pruning)

1997

"... In PAGE 16: ... Table 18 shows the values for each task-algorithm combination when pruning is turned off, with the corresponding deviations shown in Table 19. Table20 shows the costs for each task- algorithm combination when pruning is turned on, with the corresponding deviations shown in Table 21. 6 Incremental Update Cost Might one want to use the incremental ITI algorithm within a serial learning system or knowl- edge maintenance system? The primary issue is whether online learning via incremental tree revi- sion is sufficiently time efficient.... In PAGE 37: ...37 Table 21. Standard Deviation for CPU (pruning) See Table20 forassociated pointestimates Task DL DM DE IE I1 I2 C1 C2 audio-no-id 240.4 201.... ..."

Cited by 93

### Table 20. CPU (pruning)

1997

"... In PAGE 16: ... Table 18 shows the values for each task-algorithm combination when pruning is turned off, with the corresponding deviations shown in Table 19. Table20 shows the costs for each task- algorithm combination when pruning is turned on, with the corresponding deviations shown in Table 21. 6 Incremental Update Cost Might one want to use the incremental ITI algorithm within a serial learning system or knowl- edge maintenance system? The primary issue is whether online learning via incremental tree revi- sion is sufficiently time efficient.... In PAGE 37: ...37 Table 21. Standard Deviation for CPU (pruning) See Table20 forassociated pointestimates Task DL DM DE IE I1 I2 C1 C2 audio-no-id 240.4 201.... ..."

Cited by 93

### Table 7: Parallel Efficiency.

2003

"... In PAGE 25: ... In our solver, we have parallelized only the higher level algebras expecting that this will give the best granularity and will achieve good speed-ups. In Table7 we report results of parallel runs on a 18 processor SUN HPC 3500 system. This computer has 18 400MHz UltraSPARC II processors and 18 GB of shared memory.... ..."

Cited by 18

### TABLE I COST VALUES FOR DIFFERENT TERRAIN TYPES.

### Table 4. Efficiency of the predicate pruning mechanism for regression

2005

"... In PAGE 14: ... A complete search through the predicate space was then performed for each. The results are shown in Table4 . It is clear from the table that significant reduction in computation time can be achieved in practice.... ..."

Cited by 1

### Table 5: Parallel efficiency of OOPS.

"... In PAGE 9: ... As can be seen OOPS is able to solve a problem with more than a6 a7 a9 variables on HPCx in less than one hour. Table5 also gives the parallel efficiency for a smaller problem scaling from 16- 512 processors on BlueGene. OOPS achieves a parallel efficiency of 86% on 512 processors as compared to 16 processors, with the dominant factorization part of the code even achieving 98% parallel efficiency.... ..."

### Table 1: Fast, e#0Ecient low-contention parallel algorithms for several fundamental problems. For the

"... In PAGE 11: ...1 Distributive Sorting The sorting from U#280; 1#29 problem is to sort n numbers chosen uniformly at random from the range #280; 1#29. As indicated in Table1 , the best known linear work erew pram algorithm for this problem runs in O#28n #0F #29 time, for #0Cxed #0F#3E0. erew pram algorithms that run in polylog time are work ine#0Ecientby at least a p lg n lg lgn factor.... In PAGE 14: ... Our result is for distinct keys. As shown in Table1 , the best known linear work erew pram algorithm for this problem runs in O#28n #0F #29 time. 6.... In PAGE 21: ... Examples of cyclic and noncyclic permutations are given in Figure 1. As indicated in Table1 , the best known linear work random permutation algorithm for the erew pram run in O#28n #0F #29 time, for #0Cxed #0F#3E0. This is also the best bound known for the random cyclic permutation problem.... In PAGE 37: ... This paper considers #0Cve such problems | generating a random permutation, multiple compaction, distributive sorting, parallel hashing, and load balancing | and presents fast, work-optimal qrqw pram algorithms for these fundamental problems. These results are summarized in Table1 , and are contrasted with the best known erew pram algorithms for the same problems. All of our algorithms are randomized, and are of the #5CLas Vegas quot; type; they always output correct results, and obtain the stated bounds with high probability.... ..."

### Table 1: Fast, e cient low-contention parallel algorithms for several fundamental problems. For the

1996

"... In PAGE 3: ... This paper considers ve such problems | generating a random permutation, multiple compaction, distributive sorting, parallel hashing, and load balancing | and presents fast, work-optimal qrqw pram algorithms for these fundamental problems. These results are summarized in Table1 , and are contrasted with the best known erew pram algorithms for the same problems. All of our algorithms are randomized, and are of the \Las Vegas quot; type;; they always output correct results, and obtain the stated bounds with high probability.... In PAGE 19: ... Examples of cyclic and noncyclic permutations are given in Figure 1. As indicated in Table1 , the best known linear work random permutation algorithm for the erew pram run in O(n ) time, for xed gt;0. This is also the best bound known for the random cyclic permutation problem.... In PAGE 26: ... Our result is for distinct keys. As shown in Table1 , the best known linear work erew pram algorithm for this problem runs in O(n ) time. 6.... In PAGE 29: ...1 Distributive Sorting The sorting from U(0;; 1) problem is to sort n numbers chosen uniformly at random from the range (0;; 1). As indicated in Table1 , the best known linear work erew pram algorithm for this problem runs in O(n ) time, for xed gt;0. erew pram algorithms that run in polylog time are work ine cien tbyatleasta p lg n lg lgn factor.... ..."