We present the design and implementation of an autonomic state manager (ASM) tailored for integration within optimistic parallel discrete event simulation (PDES) environments based on the C programming language and the executable and linkable format (ELF), and developed for execution on ×86_64 architectures. With ASM, the state of any logical process (LP), namely the individual (concurrent) simulation unit being part of the simulation model, is allowed to be scattered on dynamically allocated memory chunks managed via standard API (e.g., malloc/free). Also, the application programmer is not required to provide any serialization/ deserialization module in order to take a checkpoint of the LP state, or to restore it in case a causality error occurs during the optimistic run, or to provide indications on which portions of the state are updated by event processing, so to allow incremental checkpointing. All these tasks are handled by ASM in a fully transparent manner via (A) runtime identification (with chunk-level granularity) of the memory map associated with the LP state, and (B) runtime tracking of the memory updates occurring within chunks belonging to the dynamic memory map. The co-existence of the incremental and non-incremental log/restore modes is achieved via dual versions of the same application code, transparently generated by ASM via compile/link time facilities. Also, the dynamic selection of the best suited log/ restore mode is actuated by ASM on the basis of an innovative modeling/optimization approach which takes into account stability of each operating mode with respect to variations of the model/environmental execution parameters.

In Parallel Discrete Event Simulation (PDES), the simulation model is partitioned into a set of distinct Logical Processes (LPs) which are allowed to concurrently execute simulation events. In this work we present an innovative approach to load-sharing on multi-core/multiprocessor machines, targeted at the optimistic PDES paradigm, where LPs are speculatively allowed to process simulation events with no preventive verification of causal consistency, and actual consistency violations (if any) are recovered via rollback techniques. In our approach, each simulation kernel instance, in charge of hosting and executing a specific set of LPs, runs a set of worker threads, which can be dynamically activated/deactivated on the basis of a distributed algorithm. The latter relies in turn on an analytical model that provides indications on how to reassign processor/core usage across the kernels in order to handle the simulation workload as efficiently as possible. We also present a real implementation of our load-sharing architecture within the ROme OpTimistic Simulator (ROOT-Sim), namely an open-source C-based simulation platform implemented according to the PDES paradigm and the optimistic synchronization approach. Experimental results for an assessment of the validity of our proposal are presented as well.

Traditionally, Logical Processes (LPs) forming a simulation model store their execution information into disjoint simulations states, forcing events exchange to communicate data between each other. In this work we propose the design and implementation of an extension to the traditional Time Warp (optimistic) synchronization protocol for parallel/distributed simulation, targeted at shared-memory/multicore machines, allowing LPs to share parts of their simulation states by using global variables. In order to preserve optimism's intrinsic properties, global variables are transparently mapped to multi-version ones, so to avoid any form of safety predicate verification upon updates. Execution's consistency is ensured via the introduction of a new rollback scheme which is triggered upon the detection of an incorrect global variable's read. At the same time, efficiency in the execution is guaranteed by the exploitation of non-blocking algorithms in order to manage the multi-version variables' lists. Furthermore, our proposal is integrated with the simulation model's code through software instrumentation, in order to allow the application-level programmer to avoid using any specific API to mark or to inform the simulation kernel of updates to global variables. Thus we support full transparency. An assessment of our proposal, comparing it with a traditional message-passing implementation of variables' multi-version is provided as well.

In this paper we address state recoverability in optimistic simulation systems by presenting an autonomic log/restore architecture. Our proposal is unique in that it jointly provides the following features: (i) log/restore operations are carried out in a completely transparent manner to the application programmer, (ii) the simulation-object state can be scattered across dynamically allocated non-contiguous memory chunks, (iii) two differentiated operating modes, incremental vs non-incremental, coexist via transparent, optimized run-time management of dual versions of the same application layer, with dynamic selection of the best suited operating mode in different phases of the optimistic simulation run, and (iv) determination of the best suited mode for any time frame is carried out on the basis of an innovative modeling/optimization approach that takes into account stability of each operating mode vs variations of the model execution parameters.

In parallel discrete event simulation techniques, the simulation model is partitioned into objects, concurrently executing events on different CPUs and/or multiple CPU-Cores.In such a context, run-time supports for logical time synchronization across the different simulation objects play a central role in determining the effectiveness of the specific parallel simulation environment. In this paper we present an experimental evaluation of the memory management capabilities offered by the ROme OpTimistic Simulator (ROOT-Sim). This is an open source parallel simulation environment transparently supporting optimistic synchronization via recoverability (based on incremental log/restore techniques) of any type of memory operation affecting the state of simulation objects, i.e., memory allocation, deallocation and update operations. The experimental study is based on a synthetic benchmark which mimics different read/write patterns inside the dynamic memory map associated with the state of simulation objects. This allows sensibility analysis of time and space effects due to the memory management subsystem while varying the type and the locality of the accesses associated with event processing.