Advanced teleprocessing systems. Semi-annual technical report, October 1, 1983-March 31, 1984

Technical Report · Sat Mar 31 04:00:00 EST 1984

OSTI ID:6086772

The idea of multiprocessing has been with us for many years. It would be good to know, however, how much gain (i.e., speed-up) is really achieved when multiprocessors are used. In this dissertation, computer job is modeled as a Directed Acyclic Graph (DAG), each node in the DAG representing a separate task that can be processed by any processor. Four parameters are used to characterize the concurrency problem which results in 16 cases. The four parameters are: (1.) How the jobs arrive: either a fixed number of jobs at time zero or jobs arriving from a Poisson source; (2.) the DAG: either the same for each job or each job randomly selecting its DAG; (3.) service time of each task: constant or exponentially distributed; (4.) the number of processors: either a fixed number or an infinite number (infinite number of processors meaning that whenever a task requires a processor, one will be available). For all cases studied, a common concurrency measure is defined that gives a comparison of how much parallelism can be achieved. The concurrency measure is obtained exactly for several cases by first converting the DAG into a Markov chain where each state represents a possible set of tasks that can be executed in parallel. From this Markov chain, and by utilizing a special feature in the chain, we are able to find the equilibrium probabilities of each state and the average time required to process a single job.

• Research Organization: California Univ., Los Angeles (USA). Dept. of Computer Science
• OSTI ID: 6086772
• Report Number(s): AD-A-161260/5/XAB
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARRAY PROCESSORS
COMPUTERS
MARKOV PROCESS
PARALLEL PROCESSING
PROBABILITY
PROGRAMMING
STOCHASTIC PROCESSES