Performance Modeling of Multiprocessor Systems with Paging.

The rapid advancement in semiconductor technology continues to change the environment in which computers are designed. As hardware costs decline, systems with multiple processors become an interesting alternative to conventional single processor system. An analytic model has been developed to describe the performance of a wide range of multiprocessor system configurations and workloads. This model deals specifically with P tightly-coupled, identical processors with shared primary and secondary memory. Secondary memory consists of a paging drum with S sectors. The workload consists of J independent, identically-distributed jobs whose faulting or IO behavior is described by both a mean lambda faultssector-time and a squared coefficient of variation K. In addition, the processing overhead for each IO request is added to a jobs execution time at a processor C sector-timesfault. The model developed provides an estimate of system throughput for various numbers of processors, jobs, and drum sectors, and for various workloads. The model can be used to examine the behavior of multiprocessor systems, including the sensitivity of system throughput to each of the system parameters and parameters trade-offs related to system performance. In particular, in a system with a fixed amount of memory, the addition of jobs to the system causes a change in the memory allocation for each job and thus modifies each jobs faulting behavior. The above formula for throughput is useful to examine the desirability of adding or subtracting jobs in such a system.