Along the years, Parallel Discrete Event Simulation (PDES) has been enriched with programming facilities to bypass state disjointness across the concurrent Logical Processes (LPs). New supports have been proposed, offering the programmer approaches alternative to message passing to code complex LPs’ relations. Along this path we find Event & Cross-State (ECS), which allows writing event handlers which can perform in-place accesses to the state of any LP, by simply relying on pointers. This programming model has been shipped with a runtime support enabling concurrent speculative execution of LPs limited to shared-memory machines. In this paper, we present the design of a middleware layer that allows ECS to be ported to distributed-memory clusters of machines. A core application of our middleware is to let ECS-coded models be hosted on top of (low-cost) resources from the Cloud. Overall, ECS-coded models no longer demand for powerful shared-memory machines to execute in reasonable time. Thanks to our solution, we retain indeed the possibility to rely on the enriched ECS programming model while still enabling deployments of PDES models on convenient (Cloudbased) infrastructures. An experimental assessment of our proposal is also provided.
Principe, M., Tocci, T., Pellegrini, A., Quaglia, F. (2018). Porting Event &Cross-State Synchronization to the Cloud. In Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (pp.177-188). Association for Computing Machinery [10.1145/3200921.3200929].
Porting Event &Cross-State Synchronization to the Cloud
Alessandro Pellegrini;Francesco Quaglia
2018-05-01
Abstract
Along the years, Parallel Discrete Event Simulation (PDES) has been enriched with programming facilities to bypass state disjointness across the concurrent Logical Processes (LPs). New supports have been proposed, offering the programmer approaches alternative to message passing to code complex LPs’ relations. Along this path we find Event & Cross-State (ECS), which allows writing event handlers which can perform in-place accesses to the state of any LP, by simply relying on pointers. This programming model has been shipped with a runtime support enabling concurrent speculative execution of LPs limited to shared-memory machines. In this paper, we present the design of a middleware layer that allows ECS to be ported to distributed-memory clusters of machines. A core application of our middleware is to let ECS-coded models be hosted on top of (low-cost) resources from the Cloud. Overall, ECS-coded models no longer demand for powerful shared-memory machines to execute in reasonable time. Thanks to our solution, we retain indeed the possibility to rely on the enriched ECS programming model while still enabling deployments of PDES models on convenient (Cloudbased) infrastructures. An experimental assessment of our proposal is also provided.File | Dimensione | Formato | |
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