Consistent and Efficient Output-Stream Management in Optimistic Simulation Platform

Francesco Antonacci, Alessandro Pellegrini, and Francesco Quaglia

Abstract:
Optimistic synchronization is considered an effective means for supporting Parallel Discrete Event Simulations. It relies on a speculative approach, where concurrent processes execute simulation events regardless of their safety, and consistency is ensured via proper rollback mechanisms, upon the a-posteriori detection of causal inconsistencies along the events’ execution path. Interactions with the outside world (e.g. generation of output streams) are a well-known problem for rollback-based systems, since the outside world may have no notion of rollback. In this context, approaches for allowing the simulation modeler to generate consistent output rely on either the usage of ad-hoc APIs (which must be provided by the underlying simulation kernel) or temporary suspension of processing activities in order to wait for the final outcome (commit/rollback) associated with a speculatively-produced output.
In this paper we present design indications and a reference implementation for an output streams’ management subsystem which allows the simulation-model writer to rely on standard output-generation libraries (e.g. stdio) within code blocks associated with event processing. Further, the subsystem ensures that the produced output is consistent, namely associated with events that are eventually committed, and system-wide ordered along the simulation time axis.
The above features jointly provide the illusion of a classical (simple to deal with) sequential programming model, which spares the developer from being aware that the simulation program is run concurrently and speculatively. We also show, via an experimental study, how the design/development optimizations we present lead to limited overhead, giving rise to the situation where the simulation run would have been carried out with near-to-zero or reduced output management cost. At the same time, the delay for materializing the output stream (making it available for any type of audit activity) is shown to be fairly limited and constant, especially for good mixtures of I/O-bound vs CPU-bound behaviors at the application level. Further, the whole output streams’ management subsystem has been designed in order to provide scalability for I/O management on clusters.

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