Moon Gi Seok, Chew Wye Chan, Wentong Cai, H. Sarjoughian, Daejin Park
Speeding up the simulation of discrete-event wafer fab models is essential because optimizing the scheduling and dispatching policies under various circumstances requires repeated evaluation of the decision candidates during parameter-space exploration. In this paper, we present a runtime abstraction-level conversion approach for discrete-event wafer-fabrication (wafer-fab) models to gain simulation speedup. During the simulation, if a machine group of the wafer fab models reaches a steady state, then the proposed approach attempts to substitute this group model with a mean-delay model (MDM) as a high abstraction level model. The MDM abstracts the detailed operations of the group's sub-component models into an average delay based on the queueing modeling, which can guarantee acceptable accuracy under steady state. The proposed abstraction-level converter (ALC) observes the queueing parameters of low-level groups to identify the convergence of each group's work-in-progress (WIP) level through a statistical test. When a group's WIP level is converged, the output-to-input couplings between the models are revised to change a wafer-lot process flow from the low-level group to a mean-delay model. When the ALC detects a divergence caused by a re-entrant flow or a machine-down, the high-level model is switched back to its corresponding low-level group model. The ALC then generates dummy wafer-lot events to synchronize the busyness of high-level steady state. The proposed method was applied to case studies of wafer-fab systems and achieves simulation speedup from 6.1 to 11.8 times with corresponding 2.5 to 5.9% degradation inaccuracy.
{"title":"Runtime Abstraction-Level Conversion of Discrete-Event Wafer-fabrication Models for Simulation Acceleration","authors":"Moon Gi Seok, Chew Wye Chan, Wentong Cai, H. Sarjoughian, Daejin Park","doi":"10.1145/3384441.3395982","DOIUrl":"https://doi.org/10.1145/3384441.3395982","url":null,"abstract":"Speeding up the simulation of discrete-event wafer fab models is essential because optimizing the scheduling and dispatching policies under various circumstances requires repeated evaluation of the decision candidates during parameter-space exploration. In this paper, we present a runtime abstraction-level conversion approach for discrete-event wafer-fabrication (wafer-fab) models to gain simulation speedup. During the simulation, if a machine group of the wafer fab models reaches a steady state, then the proposed approach attempts to substitute this group model with a mean-delay model (MDM) as a high abstraction level model. The MDM abstracts the detailed operations of the group's sub-component models into an average delay based on the queueing modeling, which can guarantee acceptable accuracy under steady state. The proposed abstraction-level converter (ALC) observes the queueing parameters of low-level groups to identify the convergence of each group's work-in-progress (WIP) level through a statistical test. When a group's WIP level is converged, the output-to-input couplings between the models are revised to change a wafer-lot process flow from the low-level group to a mean-delay model. When the ALC detects a divergence caused by a re-entrant flow or a machine-down, the high-level model is switched back to its corresponding low-level group model. The ALC then generates dummy wafer-lot events to synchronize the busyness of high-level steady state. The proposed method was applied to case studies of wafer-fab systems and achieves simulation speedup from 6.1 to 11.8 times with corresponding 2.5 to 5.9% degradation inaccuracy.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114431433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During long-term operation of a high-performance computing (HPC) system with thousands of components, many components will inevitably fail. The current trend in HPC interconnect router linkage is moving away from passive copper and toward active optical-based cables. Optical links offer greater bandwidth maximums in a smaller wire gauge, less signal loss, and lower latency over long distances and have no risk of electromagnetic interference from other nearby cables. The benefits of active optical links, however, come with a cost: an increased risk of component failure compared with that of passive copper cables. One way to increase the resilience of a network is to add redundant links; if one of a multiplicity of links between any two routers fails, a single hop path will still exist between them. But adding redundant links comes at the cost of using more router ports for router-router linkage, reducing the maximum size of the network with a fixed router radix. Alternatively, a secondary plane of routers can be added to the interconnect, keeping the number of compute node endpoints the same but where each node has multiple rails of packet injection, at least one per router plane. This multirail-multiplanar type of network interconnect allows the overall size of the network to be unchanged but results in a large performance benefit, even with lower-specification hardware, while also increasing the resilience of the network to link failure. We extend the CODES framework to enable multirail-multiplanar 1D-Dragonfly and Megafly networks and to allow for arbitrary link failure patterns with added dynamic failure-aware routing so that topology resilience can be measured. We use this extension to evaluate two similarly sized 1D-Dragonfly and Megafly networks with and without secondary router planes, and we compare their application communication performance with increasing levels of link failure.
{"title":"Evaluation of Link Failure Resilience in Multirail Dragonfly-Class Networks through Simulation","authors":"Neil McGlohon, R. Ross, C. Carothers","doi":"10.1145/3384441.3395989","DOIUrl":"https://doi.org/10.1145/3384441.3395989","url":null,"abstract":"During long-term operation of a high-performance computing (HPC) system with thousands of components, many components will inevitably fail. The current trend in HPC interconnect router linkage is moving away from passive copper and toward active optical-based cables. Optical links offer greater bandwidth maximums in a smaller wire gauge, less signal loss, and lower latency over long distances and have no risk of electromagnetic interference from other nearby cables. The benefits of active optical links, however, come with a cost: an increased risk of component failure compared with that of passive copper cables. One way to increase the resilience of a network is to add redundant links; if one of a multiplicity of links between any two routers fails, a single hop path will still exist between them. But adding redundant links comes at the cost of using more router ports for router-router linkage, reducing the maximum size of the network with a fixed router radix. Alternatively, a secondary plane of routers can be added to the interconnect, keeping the number of compute node endpoints the same but where each node has multiple rails of packet injection, at least one per router plane. This multirail-multiplanar type of network interconnect allows the overall size of the network to be unchanged but results in a large performance benefit, even with lower-specification hardware, while also increasing the resilience of the network to link failure. We extend the CODES framework to enable multirail-multiplanar 1D-Dragonfly and Megafly networks and to allow for arbitrary link failure patterns with added dynamic failure-aware routing so that topology resilience can be measured. We use this extension to evaluate two similarly sized 1D-Dragonfly and Megafly networks with and without secondary router planes, and we compare their application communication performance with increasing levels of link failure.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network emulators enable rapid prototyping and testing of applications. In a typical emulation the execution order and process execution burst lengths are managed by the host platform's operating system, largely independent of the emulator. Timer based mechanisms are typically used, but the imprecision of timer firings introduces imprecision in the advancement of time. This leads to statistical variation in behavior which is not due to the model. We describe Kronos, a small set of modifications to the Linux kernel that use precise instruction level tracking of process execution and control over execution order of containers, and so improve the mapping of executed behavior to advancement in time. This, and control of execution and placement of emulated processes in virtual time make the behavior of the emulation independent of the CPU resources of the platform which hosts the emulation. Under Kronos each process has its own virtual clock which is advanced based on a count of the number of x86 assembly instructions executed by its children. We experimentally show that Kronos is scalable, in the sense that the system behavior is accurately captured even as the size of the emulated system increases relative to fixed emulation resources. We demonstrate the impact of Kronos' time advancement precision by comparing it against emulations which like Kronos are embedded in virtual time, but unlike Kronos rely on Linux timers to control virtual machines and measure their progress in virtual time. We also present two useful applications where Kronos aids in generating high fidelity emulation results at low hardware costs: (1) analysing protocol performance and (2) enabling analysis of cyber physical control systems.
{"title":"Precise Virtual Time Advancement for Network Emulation","authors":"Vignesh Babu, D. Nicol","doi":"10.1145/3384441.3395978","DOIUrl":"https://doi.org/10.1145/3384441.3395978","url":null,"abstract":"Network emulators enable rapid prototyping and testing of applications. In a typical emulation the execution order and process execution burst lengths are managed by the host platform's operating system, largely independent of the emulator. Timer based mechanisms are typically used, but the imprecision of timer firings introduces imprecision in the advancement of time. This leads to statistical variation in behavior which is not due to the model. We describe Kronos, a small set of modifications to the Linux kernel that use precise instruction level tracking of process execution and control over execution order of containers, and so improve the mapping of executed behavior to advancement in time. This, and control of execution and placement of emulated processes in virtual time make the behavior of the emulation independent of the CPU resources of the platform which hosts the emulation. Under Kronos each process has its own virtual clock which is advanced based on a count of the number of x86 assembly instructions executed by its children. We experimentally show that Kronos is scalable, in the sense that the system behavior is accurately captured even as the size of the emulated system increases relative to fixed emulation resources. We demonstrate the impact of Kronos' time advancement precision by comparing it against emulations which like Kronos are embedded in virtual time, but unlike Kronos rely on Linux timers to control virtual machines and measure their progress in virtual time. We also present two useful applications where Kronos aids in generating high fidelity emulation results at low hardware costs: (1) analysing protocol performance and (2) enabling analysis of cyber physical control systems.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115872206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Bergmann, N. Feldkamp, Florian Conrad, S. Strassburger
This paper presents an approach for optimizing the robustness of production and logistic systems based on deep generative models, a special method of deep learning. Robustness here refers to setting controllable factors of a system in such a way that variance in the uncontrollable factors (noise) has a minimal effect on given output parameters. In a case study, the proposed method is tested and compared to a traditional method for robustness analysis. The basic idea is to use deep neural networks to generate data for experiment plans and rate them by use of a simulation model of the production system. We propose to use two Generative Adversarial Networks (GANs) to generate optimized experiment plans for the decision factors and the noise factors, respectively, in a competitive, turn-based game. In one turn, the controllable factors are optimized and the noise remains constant, and vice versa in the next turn. For the calculations of the robustness, the planned experiments are conducted and rated using a simulation model in each learning step.
{"title":"A Method for Robustness Optimization Using Generative Adversarial Networks","authors":"S. Bergmann, N. Feldkamp, Florian Conrad, S. Strassburger","doi":"10.1145/3384441.3395981","DOIUrl":"https://doi.org/10.1145/3384441.3395981","url":null,"abstract":"This paper presents an approach for optimizing the robustness of production and logistic systems based on deep generative models, a special method of deep learning. Robustness here refers to setting controllable factors of a system in such a way that variance in the uncontrollable factors (noise) has a minimal effect on given output parameters. In a case study, the proposed method is tested and compared to a traditional method for robustness analysis. The basic idea is to use deep neural networks to generate data for experiment plans and rate them by use of a simulation model of the production system. We propose to use two Generative Adversarial Networks (GANs) to generate optimized experiment plans for the decision factors and the noise factors, respectively, in a competitive, turn-based game. In one turn, the controllable factors are optimized and the noise remains constant, and vice versa in the next turn. For the calculations of the robustness, the planned experiments are conducted and rated using a simulation model in each learning step.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131929919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the significantly growing investment in quantum communi-cations, quantum key distribution (QKD), as a key application toshare a security key between two remote parties, has been deployedin urban areas and even at a continental scale. To meet the designrequirements of QKD on a quantum communication network, todayresearchers extensively conduct simulation-based evaluations in ad-dition to physical experiments for cost efficiency. A practical QKDsystem must be implemented on a large scale via a network, notjust between a few pairs of users. Existing discrete-event simulatorsoffer models for QKD hardware and protocols based on sequentialexecution. In this work, we investigate the parallel simulation ofQKD networks for scalability enhancement. Our contributions layin the exploration of QKD network characteristics to be leveragedfor parallel simulation. We also develop a parallel simulator forQKD networks with an optimized scheme for network partition.Experimental results show that to simulate a 64-node QKD net-work, our parallel simulator can complete the experiment 9 timesfaster than a sequential simulator running on the same machine.Our linear-regression-based network partition scheme can furtheraccelerate the simulation experiments up to two times than using arandomized network partition scheme.
{"title":"Parallel Simulation of Quantum Key Distribution Networks","authors":"Xiaoliang Wu, B. Zhang, Dong Jin","doi":"10.1145/3384441.3395988","DOIUrl":"https://doi.org/10.1145/3384441.3395988","url":null,"abstract":"With the significantly growing investment in quantum communi-cations, quantum key distribution (QKD), as a key application toshare a security key between two remote parties, has been deployedin urban areas and even at a continental scale. To meet the designrequirements of QKD on a quantum communication network, todayresearchers extensively conduct simulation-based evaluations in ad-dition to physical experiments for cost efficiency. A practical QKDsystem must be implemented on a large scale via a network, notjust between a few pairs of users. Existing discrete-event simulatorsoffer models for QKD hardware and protocols based on sequentialexecution. In this work, we investigate the parallel simulation ofQKD networks for scalability enhancement. Our contributions layin the exploration of QKD network characteristics to be leveragedfor parallel simulation. We also develop a parallel simulator forQKD networks with an optimized scheme for network partition.Experimental results show that to simulate a 64-node QKD net-work, our parallel simulator can complete the experiment 9 timesfaster than a sequential simulator running on the same machine.Our linear-regression-based network partition scheme can furtheraccelerate the simulation experiments up to two times than using arandomized network partition scheme.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121955818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Development of crowd evacuation systems is a challenge due to involvement of complex interrelated aspects, diversity of involved individuals and/or environment, and lack of direct evidence. Evacuation modeling and simulation is used to analyze various possible outcomes as different scenarios unfold, typically when the complexity of scenario is high. However, incorporation of different aspect categories in a unified modeling space is a challenge. In this paper, we addressed this challenge by combining individual, social and technological models of people during evacuation, while pivoting all these aspects on a common agent-based modeling framework and a grid-based hypothetical environment. By simulating these models, an insight into the effectiveness of several interesting evacuation scenarios is provided. Based on the simulation results, a couple of useful recommendations are also given. The most important recommendation is not to use potential field indicating the exits dynamics as an exit strategy particularly for a spatial complexity environment.
{"title":"An Agent-Based Model of Crowd Evacuation: Combining Individual, Social and Technological Aspects","authors":"K. Zia, A. Ferscha","doi":"10.1145/3384441.3395973","DOIUrl":"https://doi.org/10.1145/3384441.3395973","url":null,"abstract":"Development of crowd evacuation systems is a challenge due to involvement of complex interrelated aspects, diversity of involved individuals and/or environment, and lack of direct evidence. Evacuation modeling and simulation is used to analyze various possible outcomes as different scenarios unfold, typically when the complexity of scenario is high. However, incorporation of different aspect categories in a unified modeling space is a challenge. In this paper, we addressed this challenge by combining individual, social and technological models of people during evacuation, while pivoting all these aspects on a common agent-based modeling framework and a grid-based hypothetical environment. By simulating these models, an insight into the effectiveness of several interesting evacuation scenarios is provided. Based on the simulation results, a couple of useful recommendations are also given. The most important recommendation is not to use potential field indicating the exits dynamics as an exit strategy particularly for a spatial complexity environment.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Simulations and Artificial Intelligence","authors":"Canada","doi":"10.1145/3406361","DOIUrl":"https://doi.org/10.1145/3406361","url":null,"abstract":"","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125810698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Philipp Andelfinger, D. Eckhoff, Wentong Cai, A. Knoll
State fast-forwarding has been proposed as a method to reduce the computational cost of microscopic traffic simulations while retaining per-vehicle trajectories. However, since fast-forwarding relies on vehicles isolated on the road, its benefits extend only to situations of sparse traffic. In this paper, we propose fast-forwarding of vehicle clusters by training artificial neural networks to capture the interactions between vehicles across multiple simulation time steps. We explore various configurations of neural networks in light of the trade-off between accuracy and performance. Measurements in road network simulations demonstrate that cluster fast-forwarding can substantially outperform both time-driven state updates and single-vehicle fast-forwarding, while introducing only a small deviation in travel times.
{"title":"Fast-Forwarding of Vehicle Clusters in Microscopic Traffic Simulations","authors":"Philipp Andelfinger, D. Eckhoff, Wentong Cai, A. Knoll","doi":"10.1145/3384441.3395975","DOIUrl":"https://doi.org/10.1145/3384441.3395975","url":null,"abstract":"State fast-forwarding has been proposed as a method to reduce the computational cost of microscopic traffic simulations while retaining per-vehicle trajectories. However, since fast-forwarding relies on vehicles isolated on the road, its benefits extend only to situations of sparse traffic. In this paper, we propose fast-forwarding of vehicle clusters by training artificial neural networks to capture the interactions between vehicles across multiple simulation time steps. We explore various configurations of neural networks in light of the trade-off between accuracy and performance. Measurements in road network simulations demonstrate that cluster fast-forwarding can substantially outperform both time-driven state updates and single-vehicle fast-forwarding, while introducing only a small deviation in travel times.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123674317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The authors request for this paper the following badges: (1)Artifacts Available(2)Artifacts Evaluated ? Functional(3)Artifacts Evaluated? Reusable(4)Results Replicated. After the review process, all of them were assigned, as the artifact met all the requirements.
{"title":"Reproducibility Report for the Paper: Partial Evaluation via Code Generation for Static Stochastic Reaction Network Models","authors":"Stefano Carnà","doi":"10.1145/3384441.3396228","DOIUrl":"https://doi.org/10.1145/3384441.3396228","url":null,"abstract":"The authors request for this paper the following badges: (1)Artifacts Available(2)Artifacts Evaluated ? Functional(3)Artifacts Evaluated? Reusable(4)Results Replicated. After the review process, all of them were assigned, as the artifact met all the requirements.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115740531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper introduced a novel state-rollback mechanism named approximated rollbacks for speculative parallel discrete event simulators. The artifact of the paper is available online and is properly documented. It contains a simulation framework comprising of a parallel discrete event simulator called ROOT-Sim and a set of Application Programming Interfaces (APIs) for approximated rollbacks. This simulation framework can be employed in a wide range of discrete-event-based simulation scenarios. The experiment results were successfully replicated. Therefore, I assign all the functional, reusable, available, and results replicated badges to this paper.
{"title":"Reproducibility Report for the Paper: Approximated Rollbacks","authors":"Jiajian Xiao","doi":"10.1145/3384441.3396229","DOIUrl":"https://doi.org/10.1145/3384441.3396229","url":null,"abstract":"The paper introduced a novel state-rollback mechanism named approximated rollbacks for speculative parallel discrete event simulators. The artifact of the paper is available online and is properly documented. It contains a simulation framework comprising of a parallel discrete event simulator called ROOT-Sim and a set of Application Programming Interfaces (APIs) for approximated rollbacks. This simulation framework can be employed in a wide range of discrete-event-based simulation scenarios. The experiment results were successfully replicated. Therefore, I assign all the functional, reusable, available, and results replicated badges to this paper.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"285 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133975070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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