Real-Time Online Interactive Applications, e.g., multiplayer online games, connect a high number of users who interact with the application and with each other in real time, i.e., a response to a user's input should happen virtually immediately. We address the problem of reproducing the communication behavior of such applications in order to study the effect of various design decisions (application logic, underlying infrastructure, network protocols, etc.) at early stages of application development. We develop a flexible, lightweight simulator as an alternative to the state-of-the-art simulation approaches that rely on the recorded communication traffic of real applications. The advantage of our approach is that we can easily adapt to a particular application design and its underlying infrastructure and we can measure various communication metrics, without relying on existing application prototypes and real users. Our experiments demonstrate that the simulator realistically reproduces communication behavior for high numbers of users and that simulation results are very near to the communication patterns of recorded communication traffic, e.g., for the commercially successful multiplayer game Counter Strike.
{"title":"Towards Simulating the Communication Behavior of Real-Time Interactive Applications","authors":"Tim Humernbrum, C. Ahlbrand, S. Gorlatch","doi":"10.1145/3064911.3064931","DOIUrl":"https://doi.org/10.1145/3064911.3064931","url":null,"abstract":"Real-Time Online Interactive Applications, e.g., multiplayer online games, connect a high number of users who interact with the application and with each other in real time, i.e., a response to a user's input should happen virtually immediately. We address the problem of reproducing the communication behavior of such applications in order to study the effect of various design decisions (application logic, underlying infrastructure, network protocols, etc.) at early stages of application development. We develop a flexible, lightweight simulator as an alternative to the state-of-the-art simulation approaches that rely on the recorded communication traffic of real applications. The advantage of our approach is that we can easily adapt to a particular application design and its underlying infrastructure and we can measure various communication metrics, without relying on existing application prototypes and real users. Our experiments demonstrate that the simulator realistically reproduces communication behavior for high numbers of users and that simulation results are very near to the communication patterns of recorded communication traffic, e.g., for the commercially successful multiplayer game Counter Strike.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128434436","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}
Smart city projects, infrastructure planning, and traffic engineering are some of the applications where traffic simulations are playing an increasingly important role. Although many traffic simulators, commercial or open-sourced, are available at our disposal today, choosing the one that best fits a user's requirements is usually not possible by taking into account only the qualitative aspects and features of the simulator. In resource-constrained simulation platforms, performing traffic simulations with less memory usage and faster execution time is always highly coveted. In this paper, we propose a quantitative benchmarking approach for evaluating the performance of traffic simulator, based on commonplace scenarios and real-life city maps.
{"title":"Towards a Benchmark for the Quantitative Evaluation of Traffic Simulators","authors":"Priya Toshniwal, Masatoshi Hanai, Elvis S. Liu","doi":"10.1145/3064911.3064928","DOIUrl":"https://doi.org/10.1145/3064911.3064928","url":null,"abstract":"Smart city projects, infrastructure planning, and traffic engineering are some of the applications where traffic simulations are playing an increasingly important role. Although many traffic simulators, commercial or open-sourced, are available at our disposal today, choosing the one that best fits a user's requirements is usually not possible by taking into account only the qualitative aspects and features of the simulator. In resource-constrained simulation platforms, performing traffic simulations with less memory usage and faster execution time is always highly coveted. In this paper, we propose a quantitative benchmarking approach for evaluating the performance of traffic simulator, based on commonplace scenarios and real-life city maps.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"50 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131550481","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}
We present a novel approach for approximating objective functions in arbitrary deterministic and stochastic multi-objective blackbox simulations. Usually, simulated-based optimization approaches require pre-defined objective functions for optimization techniques in order to find a local or global minimum of the specified simulation objectives and multi-objective constraints. Due to the increasing complexity of state-of-the-art simulations, such objective functions are not always available, leading to so-called blackbox simulations. In contrast to existing approaches, we approximate the objective functions and design space for deterministic and stochastic blackbox simulations, even for convex and concave Pareto fronts, thus enabling optimization for arbitrary simulations. Additionally, Pareto gradient information can be obtained from our design space approximation. Our approach gains its efficiency from a novel gradient-based sampling of the parameter space in combination with a density-based clustering of sampled objective function values, resulting in a B-spline surface approximation of the feasible design space. We have applied our new method to several benchmarks and the results show that our approach is able to efficiently approximate arbitrary objective functions. Additionally, the computed multi-objective solutions in our evaluation studies are close to the Pareto front.
{"title":"GDS: Gradient Based Density Spline Surfaces For Multiobjective Optimization In Arbitrary Simulations","authors":"Patrick Lange, René Weller, G. Zachmann","doi":"10.1145/3064911.3064917","DOIUrl":"https://doi.org/10.1145/3064911.3064917","url":null,"abstract":"We present a novel approach for approximating objective functions in arbitrary deterministic and stochastic multi-objective blackbox simulations. Usually, simulated-based optimization approaches require pre-defined objective functions for optimization techniques in order to find a local or global minimum of the specified simulation objectives and multi-objective constraints. Due to the increasing complexity of state-of-the-art simulations, such objective functions are not always available, leading to so-called blackbox simulations. In contrast to existing approaches, we approximate the objective functions and design space for deterministic and stochastic blackbox simulations, even for convex and concave Pareto fronts, thus enabling optimization for arbitrary simulations. Additionally, Pareto gradient information can be obtained from our design space approximation. Our approach gains its efficiency from a novel gradient-based sampling of the parameter space in combination with a density-based clustering of sampled objective function values, resulting in a B-spline surface approximation of the feasible design space. We have applied our new method to several benchmarks and the results show that our approach is able to efficiently approximate arbitrary objective functions. Additionally, the computed multi-objective solutions in our evaluation studies are close to the Pareto front.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120919433","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 set of events available for execution in a Parallel Discrete Event Simulation (PDES) are known as the pending event set. In a Time Warp synchronized simulation engine, these pending events are scheduled for execution in an aggressive manner that does not strictly enforce the causal relations between events. One of the key principles of Time Warp is that this relaxed causality will result in the processing of events in a manner that implicitly satisfies their causal order without paying the overhead costs of a strict enforcement of their causal order. On a shared memory platform the event scheduler generally attempts to schedule all available events in their Least TimeStamp First (LTSF) order to facilitate event processing in their causal order. By following an LTSF scheduling policy, a Time Warp scheduler can generally process events so that: (i) the critical path of the event timestamps is scheduled as early as possible, and (ii) causal violations occur infrequently. While this works effectively to minimize rollback (triggered by causal violations), as the number of parallel threads increases, the contention to the shared data structures holding the pending events can have significant negative impacts on overall event processing throughput. This work examines the application of profile data taken from Discrete-Event Simulation (DES) models to drive the simulation kernel optimization process. In particular, we take profile data about events in the schedule pool from three DES models to derive alternate scheduling possibilities in a Time Warp simulation kernel. Profile data from the studied DES models suggests that in many cases each Logical Process (LP) in a simulation will have multiple events that can be dequeued and executed as a set. In this work, we review the profile data and implement group event scheduling strategies based on this profile data. Experimental results show that event group scheduling can help alleviate contention and improve performance. However, the size of the event groups matters, small groupings can improve performance, larger groupings can trigger more frequent causal violations and actually slow the parallel simulation.
{"title":"Quantitative Driven Optimization of a Time Warp Kernel","authors":"Sounak Gupta, P. Wilsey","doi":"10.1145/3064911.3064932","DOIUrl":"https://doi.org/10.1145/3064911.3064932","url":null,"abstract":"The set of events available for execution in a Parallel Discrete Event Simulation (PDES) are known as the pending event set. In a Time Warp synchronized simulation engine, these pending events are scheduled for execution in an aggressive manner that does not strictly enforce the causal relations between events. One of the key principles of Time Warp is that this relaxed causality will result in the processing of events in a manner that implicitly satisfies their causal order without paying the overhead costs of a strict enforcement of their causal order. On a shared memory platform the event scheduler generally attempts to schedule all available events in their Least TimeStamp First (LTSF) order to facilitate event processing in their causal order. By following an LTSF scheduling policy, a Time Warp scheduler can generally process events so that: (i) the critical path of the event timestamps is scheduled as early as possible, and (ii) causal violations occur infrequently. While this works effectively to minimize rollback (triggered by causal violations), as the number of parallel threads increases, the contention to the shared data structures holding the pending events can have significant negative impacts on overall event processing throughput. This work examines the application of profile data taken from Discrete-Event Simulation (DES) models to drive the simulation kernel optimization process. In particular, we take profile data about events in the schedule pool from three DES models to derive alternate scheduling possibilities in a Time Warp simulation kernel. Profile data from the studied DES models suggests that in many cases each Logical Process (LP) in a simulation will have multiple events that can be dequeued and executed as a set. In this work, we review the profile data and implement group event scheduling strategies based on this profile data. Experimental results show that event group scheduling can help alleviate contention and improve performance. However, the size of the event groups matters, small groupings can improve performance, larger groupings can trigger more frequent causal violations and actually slow the parallel simulation.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134234678","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: Keynote I","authors":"Wentong Cai","doi":"10.1145/3254048","DOIUrl":"https://doi.org/10.1145/3254048","url":null,"abstract":"","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131969509","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}
In this paper, we present initial experiences implementing a general Parallel Discrete Event Simulation (PDES) accelerator on a Field Programmable Gate Array (FPGA). The accelerator can be specialized to any particular simulation model by defining the object states and the event handling logic, which are then synthesized into a custom accelerator for the given model. The accelerator consists of several event processors that can process events in parallel while maintaining the dependencies between them. Events are automatically sorted by a self-sorting event queue. The accelerator supports optimistic simulation by automatically keeping track of event history and supporting rollbacks. The architecture is limited in scalability locally by the communication and port bandwidth of the different structures. However, it is designed to allow multiple accelerators to be connected together to scale up the simulation. We evaluate the design and explore several design tradeoffs and optimizations. We show the accelerator can scale to 64 concurrent event processors relative to the performance of a single event processor.
{"title":"PDES-A: a Parallel Discrete Event Simulation Accelerator for FPGAs","authors":"Shafiur Rahman, N. Abu-Ghazaleh, W. Najjar","doi":"10.1145/3064911.3064930","DOIUrl":"https://doi.org/10.1145/3064911.3064930","url":null,"abstract":"In this paper, we present initial experiences implementing a general Parallel Discrete Event Simulation (PDES) accelerator on a Field Programmable Gate Array (FPGA). The accelerator can be specialized to any particular simulation model by defining the object states and the event handling logic, which are then synthesized into a custom accelerator for the given model. The accelerator consists of several event processors that can process events in parallel while maintaining the dependencies between them. Events are automatically sorted by a self-sorting event queue. The accelerator supports optimistic simulation by automatically keeping track of event history and supporting rollbacks. The architecture is limited in scalability locally by the communication and port bandwidth of the different structures. However, it is designed to allow multiple accelerators to be connected together to scale up the simulation. We evaluate the design and explore several design tradeoffs and optimizations. We show the accelerator can scale to 64 concurrent event processors relative to the performance of a single event processor.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133458989","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}
Current cloud rendering systems are expensive in terms of data storage, rendering computation, and networking transmission. In this paper, we propose a novel framework for lightweight and realistic WebSIM rendering based on cloud baking. Different from the existing cloud rendering systems that render full-frame image sequences, we propose that global illumination (GI) maps are baked occasionally at the server side. Our proposed framework consists of three key stages. First, the GI maps are re-baked only when the users change the WebSIM scene or the lighting. Then, after re-baking, these GI maps with indirect illumination are encoded and transferred to the client's web browsers using H.264. Finally, these GI maps are decoded and blended to produce rather realistic illuminating effects with WebGL direct illuminations. Compared with cloud rendering techniques, our system is lightweight, as it consumes much fewer resources at the cloud server in terms of both data and rendering. It provides a highly efficient, high-quality, and low-cost solution to WebSIM online interactive rendering. A prototype has been implemented, and we showed that it is able to achieve real-time rendering performance and satisfactory visual effects on web browsers, similar to popular offline rendering engines.
{"title":"Lightweight WebSIM Rendering Framework Based on Cloud-Baking","authors":"Chang Liu, Jinyuan Jia, Qian Zhang, Lei Zhao","doi":"10.1145/3064911.3064933","DOIUrl":"https://doi.org/10.1145/3064911.3064933","url":null,"abstract":"Current cloud rendering systems are expensive in terms of data storage, rendering computation, and networking transmission. In this paper, we propose a novel framework for lightweight and realistic WebSIM rendering based on cloud baking. Different from the existing cloud rendering systems that render full-frame image sequences, we propose that global illumination (GI) maps are baked occasionally at the server side. Our proposed framework consists of three key stages. First, the GI maps are re-baked only when the users change the WebSIM scene or the lighting. Then, after re-baking, these GI maps with indirect illumination are encoded and transferred to the client's web browsers using H.264. Finally, these GI maps are decoded and blended to produce rather realistic illuminating effects with WebGL direct illuminations. Compared with cloud rendering techniques, our system is lightweight, as it consumes much fewer resources at the cloud server in terms of both data and rendering. It provides a highly efficient, high-quality, and low-cost solution to WebSIM online interactive rendering. A prototype has been implemented, and we showed that it is able to achieve real-time rendering performance and satisfactory visual effects on web browsers, similar to popular offline rendering engines.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":" 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113949178","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: Paper Session 6 Modeling and Simulation Methods","authors":"C. Carothers","doi":"10.1145/3254055","DOIUrl":"https://doi.org/10.1145/3254055","url":null,"abstract":"","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"341 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116477039","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 parallel execution of discrete-event simulations on commodity GPUs has been shown to achieve high event rates. Most previous proposals have focused on conservative synchronization, which typically extracts only limited parallelism in cases of low event density in simulated time. We present the design and implementation of an optimistic fully GPU-based parallel discrete-event simulator based on the Time Warp synchronization algorithm. The optimistic simulator implementation is compared with an otherwise identical implementation using conservative synchronization. Our evaluation shows that in most cases, the increase in parallelism when using optimistic synchronization significantly outweighs the increased overhead for state keeping and rollbacks. To reduce the cost of state keeping, we show how XORWOW, the default pseudo-random number generator in CUDA, can be reversed based solely on its current state. Since the optimal configuration of multiple performance-critical simulator parameters depends on the behavior of the simulation model, these parameters are adapted dynamically based on performance measurements and heuristic optimization at runtime. We evaluate the simulator using the PHOLD benchmark model and a simplified model of peer-to-peer networks using the Kademlia protocol. On a commodity GPU, the optimistic simulator achieves event rates of up to 81.4 million events per second and a speedup of up to 3.6 compared with conservative synchronization.
{"title":"Time Warp on the GPU: Design and Assessment","authors":"Xinhu Liu, Philipp Andelfinger","doi":"10.1145/3064911.3064912","DOIUrl":"https://doi.org/10.1145/3064911.3064912","url":null,"abstract":"The parallel execution of discrete-event simulations on commodity GPUs has been shown to achieve high event rates. Most previous proposals have focused on conservative synchronization, which typically extracts only limited parallelism in cases of low event density in simulated time. We present the design and implementation of an optimistic fully GPU-based parallel discrete-event simulator based on the Time Warp synchronization algorithm. The optimistic simulator implementation is compared with an otherwise identical implementation using conservative synchronization. Our evaluation shows that in most cases, the increase in parallelism when using optimistic synchronization significantly outweighs the increased overhead for state keeping and rollbacks. To reduce the cost of state keeping, we show how XORWOW, the default pseudo-random number generator in CUDA, can be reversed based solely on its current state. Since the optimal configuration of multiple performance-critical simulator parameters depends on the behavior of the simulation model, these parameters are adapted dynamically based on performance measurements and heuristic optimization at runtime. We evaluate the simulator using the PHOLD benchmark model and a simplified model of peer-to-peer networks using the Kademlia protocol. On a commodity GPU, the optimistic simulator achieves event rates of up to 81.4 million events per second and a speedup of up to 3.6 compared with conservative synchronization.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122613587","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: Paper Session 3 Performance Modeling and Simulation","authors":"D. Nicol","doi":"10.1145/3254052","DOIUrl":"https://doi.org/10.1145/3254052","url":null,"abstract":"","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115124873","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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