Paper Info
Title
Hybrid CPU-GPU Distributed Framework for Large Scale Mobile Networks Simulation
Abstract
Most of the existing packet-level simulation tools are designed to perform experiments modeling a small to medium scale networks. The main reason of this limitation is the amount of available computation power and memory in quasi mono-process simulation environment. To enable efficient packet-level simulation for large scale scenario, we introduce a new CPU-GPU co-simulation framework where synchronization and experiment design are performed on CPU and node's processes are executed in parallel on GPU according to the master/worker model [13]. The framework is developed using Compute-Unified Device Architecture (CUDA) and denoted as Cunetsim, CUDA network simulator. To study the performance gain when GPU is used, we also introduce the CPU-legacy version of Cunetsim optimized for multi-core architecture. In this work, we present Cunetsim architecture, design concept, and features. We evaluate the performance of Cunetsim (both versions) compared to Sinalgo and NS-3 using benchmark scenarios. Evaluation results show that Cunetsim execution time remains stable and that it achieves significantly lower computation time than CPU-based simulators for both static and mobile networks with no degradation in the accuracy of the results. We also study the impact of the hardware configuration on the performance gain and the simulation correctness. Cunetsim presents a proof of concept, demonstrating the feasibility of a fully GPU-based simulation rather than GPUoffloading or partial acceleration, through adequate architecture.
Year
DOI
Venue
2012
10.1109/DS-RT.2012.15
Distributed Simulation and Real Time Applications
Keywords
Field
DocType
distributed processing,graphics processing units,mobile radio,parallel architectures,telecommunication computing,CPU-GPU cosimulation,CPU-legacy version,CUDA network simulator,Cunetsim architecture,GPU-based simulation,compute-unified device architecture,hybrid CPU-GPU distributed framework,large scale mobile network,master-worker model,multicore architecture,packet-level simulation tool,quasi monoprocess simulation,small-to-medium scale network,CUDA,GPGPU,Hybrid simulation,Large scale,network simulation,wireless simulation
Mobile radio,Synchronization,Computer science,CUDA,Parallel computing,Correctness,Network simulation,Real-time computing,Proof of concept,Computational science,General-purpose computing on graphics processing units,Computation
Conference
ISSN
ISBN
Citations 
1550-6525
978-1-4673-2954-5
14
PageRank 
References 
Authors
0.82
10
3
Name
Order
Citations
PageRank
Ben Romdhanne Bilel1140.82
Navid Nikaein285878.83
Mohamed Said Mosli Bouksiaa3140.82