Simulation Study of a Parallel Processor with Unbalanced Loads

摘要

The purpose of this thesis was twofold: to estimate the impact of unbalanced computational loads on a parallel processing architecture via Monte Carlo simulation; and second to investigate the impact of representing the dynamics of the parallel processing problem via animated simulation. It is constrained to the hypercube architecture in which each node is connected in a predetermined topology and allowed to communicate to other nodes through calls to the operating system. Routing of messages through the network is fixed and specified within the operating system. Message transmission preempts nodal processing causing internodal communications to complicate the concurrent operation of the network. Two independent variables are defined: 1) the degree of imbalance characterizes the nature or severity of the load imbalance, and 2) the degree of locality characterizes the node loadings with respect to node locations across the cube. A SLAM II simulation model of a generic 16 node hypercube was constructed in which each node processes a predetermined number of computational tasks and, following each task, sends a message to a single randomly chosen receiver node. An experiment was designed in which the independent variables, degree of imbalance and degree of locality were varied across two computation-to-IO ratios to determine their separate and interactive effects on the dependent variable, job speedup. ANOVA and regression techniques were used to estimate the relationship between load imbalance, locality, computation-to-IO ratio, and their interactions to job speedup. Results show that load imbalance severely impacts a parallel processor's performance.