### Table 1: Summary of Basic Multiprocessor Scheduling Theorems

1995

"... In PAGE 16: ... The complexity results from deterministic scheduling theory for multiprocessing where tasks are non-preemptive, have a partial order among themselves, have resource constraints (even a single resource constraint), and have a single deadline show that almost all the problems are NP-complete. To delineate the boundary between polynomial and NP-hard problems and to present basic results that every real-time designer should know, we list the following theorems without proof and compare them in Table1 . The metric used in the following theorems is the amount of computation time required for determining a schedule which satis es the partial order and resource constraints, and completes all required processing before a given xed deadline.... ..."

Cited by 94

### Table 1. CPU time for Parallel External A* in GIOP on a multiprocessor machine.

2006

Cited by 9

### Table 2. CPU time for Parallel External A* in Optical Telegraph on a multiprocessor machine.

2006

Cited by 9

### Table 6: Task parallel performance on Thinking Machines CM-5 message-passing distributed- memory multiprocessor

### Table 3: Complexity results for the general parallel machine scheduling problems.

### Table 5: Description of number of machines allotted for each th j level

"... In PAGE 81: ... Table 4 shows the set of demand values applied for twelve periods, for each th i level. Table5 shows the number of machines allotted for each th j level. The general arrangement of the two-factor factorial design is described in Table 6.... ..."

### Table 3: Data parallel performance on Thinking Machines CM-5 message-passing distributed-memory multiprocessor Circuit Processors

"... In PAGE 22: ... It is important to notice that there are cases in which a combination of data and task parallelism provides better performance over either type of parallelism individually. Compared to Table3 , the results on the 128 processor runs show that the combined task... ..."