DONS: Fast and Affordable Discrete Event Network Simulation with Automatic Parallelization

Abstract

Discrete Event Simulation (DES) is an essential tool for network practitioners. Unfortunately, existing DES simulators cannot achieve satisfactory performance at the scale of modern networks. Recent work has attempted to address these challenges by reducing the traffic processed via novel approximation techniques; however, we argue in this paper that much of the slowdown of existing DES simulators is due to their underlying software architecture.Using ideas from high-throughput simulation of virtual worlds in gaming, this paper presents a fundamental redesign of DES network simulator, DONS, that marries domain-specific aspects of packet-level network simulation with recent advances in data-oriented design. DONS can automatically parallelize simulation within and across servers to achieve high core utilization, low cache miss rate, and high memory efficiency. On a relatively weak ARM-based laptop (MacBook Air (M1, 2020)), DONS can simulate one second of a 100 Gbps, 1024-server data center in 22 minutes (a speedup of 21× compared to OMNeT++). On a cluster of CPU-based servers, DONS can achieve a speedup of 65×, matching the order of magnitude of recent GPU-accelerated deep learning performance estimators, but without any loss of accuracy.