Granular Time Warp Objects. Marziale, N., Nobilia, F., Pellegrini, A., & Quaglia, F. In Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, of PADS, pages 57–68, May, 2016. ACM.
doi  abstract   bibtex   
A recent trend has shown the relevance of PDES paradigms where simulation objects are no longer seen as fully disjoint entities only interacting via events' scheduling. Particularly, mutual cross-state access (as a form of state sharing) can represent an approach enabling the simplification of the programmer's job. In this article, we present a multi-core oriented Time Warp platform supporting so called granular objects, where cross-state access is transparently enabled jointly with the dynamic clustering (granulation) of objects into groups depending on the volume of mutual state accesses along phases of the model execution. Each group represents an island where activities are sequentially dispatched in timestamp order. Concurrency is still preserved by enabling the optimistic execution of the different islands. Granulated objects do not pay synchronization costs due to mutual causal inconsistencies. Also, the underlying Time Warp platform does not pay memory management (e.g. memory access tracing) overheads to determine that mutual accesses are taking place within a group. Overall, the platform transparently (and dynamically) determines a well-suited granulation of the overall model state, and a corresponding level of concurrency, depending on the actual state access pattern by the simulation code. As far as we know, this is the first study where the problem of clustering Time Warp simulation objects is addressed for the case of in-place cross-object state accesses by the application code, and where dynamic granulation of multiple objects in a larger one is supported in a fully transparent manner. We integrated our proposal in the open source ROOT-Sim platform.
@InProceedings{Mar16,
  author    = {Marziale, Nazzareno and Nobilia, Francesco and Pellegrini, Alessandro and Quaglia, Francesco},
  booktitle = {Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation},
  title     = {Granular Time Warp Objects},
  year      = {2016},
  month     = may,
  pages     = {57--68},
  publisher = {ACM},
  series    = {PADS},
  abstract  = {A recent trend has shown the relevance of PDES paradigms where simulation objects are no longer seen as fully disjoint entities only interacting via events' scheduling. Particularly, mutual cross-state access (as a form of state sharing) can represent an approach enabling the simplification of the programmer's job. In this article, we present a multi-core oriented Time Warp platform supporting so called granular objects, where cross-state access is transparently enabled jointly with the dynamic clustering (granulation) of objects into groups depending on the volume of mutual state accesses along phases of the model execution. Each group represents an island where activities are sequentially dispatched in timestamp order. Concurrency is still preserved by enabling the optimistic execution of the different islands. Granulated objects do not pay synchronization costs due to mutual causal inconsistencies. Also, the underlying Time Warp platform does not pay memory management (e.g. memory access tracing) overheads to determine that mutual accesses are taking place within a group. Overall, the platform transparently (and dynamically) determines a well-suited granulation of the overall model state, and a corresponding level of concurrency, depending on the actual state access pattern by the simulation code. As far as we know, this is the first study where the problem of clustering Time Warp simulation objects is addressed for the case of in-place cross-object state accesses by the application code, and where dynamic granulation of multiple objects in a larger one is supported in a fully transparent manner. We integrated our proposal in the open source ROOT-Sim platform.},
  doi       = {10.1145/2901378.2901390},
  location  = {Banff, Canada},
}
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