Performance scalability in multiprocessor systems with resource contention

Multiple processes may contend for shared resources such as variables stored in the shared memory of a multiprocessor system. Mechanisms required to preserve data consistency on such systems often lead do a decrease in system performance. This research focuses on controlling shared resource contention for achieving high capacity and scalability in multiprocessor based applications that include telephone switches and real time databases. Both reengineering of existing code as well as appropriate scheduling of the processes are two viable methods for controlling memory contention. Emphasis is placed on the second approach. Based on analytic models, three different scheduling approaches are compared. The numerical results obtained from the model provide insights into system behavior and highlight the important attributes of each strategy. A hybrid approach that combines the good attributes of a number of these strategies is proposed and analyzed. The results of this research are useful mainly to designers of software for multiprocessor based telecommunication and other embedded systems