Parallel DEVS: a parallel, hierarchical, modular, modeling formalism
WSC '94 Proceedings of the 26th conference on Winter simulation
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Theory of Modeling and Simulation
Theory of Modeling and Simulation
N-dimensional Cell-DEVS Models
Discrete Event Dynamic Systems
The DEVS Environment for High-Performance Modeling and Simulation
IEEE Computational Science & Engineering
Implementing Parallel Cell-DEVS
ANSS '03 Proceedings of the 36th annual symposium on Simulation
Introduction to the cell multiprocessor
IBM Journal of Research and Development - POWER5 and packaging
Compilation for explicitly managed memory hierarchies
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
CellSs: making it easier to program the cell broadband engine processor
IBM Journal of Research and Development
Scientific computing Kernels on the cell processor
International Journal of Parallel Programming
Orchestrating the execution of stream programs on multicore platforms
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Scientific Programming - High Performance Computing with the Cell Broadband Engine
Discrete-Event Modeling and Simulation: A Practitioner's Approach
Discrete-Event Modeling and Simulation: A Practitioner's Approach
Modeling multigrain parallelism on heterogeneous multi-core processors: a case study of the cell BE
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
Accelerating large-scale DEVS-based simulation on the cell processor
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Parallel discrete event simulation for DEVS cellular models using a GPU
Proceedings of the 2012 Symposium on High Performance Computing
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We propose a computing technique for efficient parallel simulation of compute-intensive DEVS models on the IBM Cell processor, combining multi-grained parallelism and various optimizations to speed up the event execution. Unlike most existing parallelization strategies, our approach explicitly exploits the massive fine-grained event-level parallelism inherent in the simulation process, while most of the logical processes are virtualized, making the achievable parallelism more deterministic and predictable. Together, the parallelization and optimization strategies produced promising experimental results, accelerating the simulation of a 3D environmental model by a factor of up to 33.06. The proposed methods can also be applied to other multicore and shared-memory architectures.