Title :
Response time analysis of parallel computer and storage systems
Author :
Varki, Elizabeth
Author_Institution :
Dept. of Comput. Sci., New Hampshire Univ., Durham, NH, USA
fDate :
11/1/2001 12:00:00 AM
Abstract :
Fork-join structures have gained increased importance in recent years as a means of modeling parallelism in computer and storage systems. The basic fork-join model is one in which a job arriving at a parallel system splits into K independent tasks that are assigned to K unique, homogeneous servers. In the paper, a simple response time approximation is derived for parallel systems with exponential service time distributions. The approximation holds for networks modeling several devices, both parallel and nonparallel. (In the case of closed networks containing a stand-alone parallel system, a mean response time bound is derived.) In addition, the response time approximation is extended to cover the more realistic case wherein a job splits into an arbitrary number of tasks upon arrival at a parallel system. Simulation results for closed networks with stand-alone parallel subsystems and exponential service time distributions indicate that the response time approximation is, on average, within 3 percent of the seeded response times. Similarly, simulation results with nonexponential distributions also indicate that the response time approximation is close to the seeded values. Potential applications of our results include the modeling of data placement in disk arrays and the execution of parallel programs in multiprocessor and distributed systems
Keywords :
Markov processes; graph theory; parallel processing; performance evaluation; probability; queueing theory; closed networks; data placement; disk arrays; distributed systems; exponential service time distributions; fork-join structures; homogeneous servers; mean response time bound; multiprocessor systems; nonexponential distributions; parallel computer systems; parallel programs; parallel storage systems; parallelism; response time approximation; stand-alone parallel system; Application software; Computational modeling; Computer networks; Concurrent computing; Delay; Helium; Network servers; Parallel processing; Power system modeling; Predictive models;
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on