Modeling Cost / Performance of a Parallel ComputerSimulatorBabak

NOTE: This is a preliminary release of an article accepted by the ACM Transactions on Modeling and Computer Simulation. The deenitive version is currently in production at ACM and, when released, will supersede this version. use is granted without fee provided that copies are not made or distributed for proot or direct commercial advantage and that copies show this notice on the rst page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior speciic permission and/or a fee. Permissions may be requested from Publications Dept, This paper examines the cost/performance of simulating a hypothetical target parallel computer using a commercial host parallel computer. We address the question of whether parallel simulation is simply faster than sequential simulation, or if it is also more cost-eeective. To answer this, we develop a performance model of the Wisconsin Wind Tunnel (WWT), a system that simulates cache-coherent shared-memory machines on a message-passing Thinking Machines CM-5. The performance model uses Kruskal and Weiss's fork-join model to account for the eeect of event processing time variability on WWT's conservative xed-window simulation algorithm. A generalization of Thi ebaut and Stone's footprint model accurately predicts the eeect of cache interference on the CM-5. The model is calibrated using parameters extracted from a fully-parallel simulation (p = N), and validated by measuring the speedup as the number of processors (p) ranges from one to the number of target nodes (N). Together with simple cost models, the performance model indicates that for target system sizes of 32 nodes and larger, parallel simulation is more cost-eeective than sequential simulation. The key intuition behind this result is that large simulations require large memories, which dominate the cost of a uniprocessor; parallel computers allow multiple processors to simultaneously access this large memory. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the oocial policies or endorsements, either expressed or implied, of the Wright Laboratory Avionics Directorate or the U.S. Government. An earlier version of this manuscript appears in Falsaa and …