Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation最新文献

Machine Learning for Interconnect Network Traffic Forecasting: Investigation and Exploitation 互联网络流量预测的机器学习:研究与开发

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591123

Xiongxiao Xu, Xin Wang, Elkin Cruz-Camacho, Christopher D. Carothers, Kevin A. Brown, Robert B. Ross, Z. Lan, Kai Shu

{"title":"Machine Learning for Interconnect Network Traffic Forecasting: Investigation and Exploitation","authors":"Xiongxiao Xu, Xin Wang, Elkin Cruz-Camacho, Christopher D. Carothers, Kevin A. Brown, Robert B. Ross, Z. Lan, Kai Shu","doi":"10.1145/3573900.3591123","DOIUrl":"https://doi.org/10.1145/3573900.3591123","url":null,"abstract":"Interconnect networks play a key role in high-performance computing (HPC) systems. Parallel discrete event simulation (PDES) has been a long-standing pillar for studying large-scale networking systems by replicating the real-world behaviors of HPC facilities. However, the simulation requirements and computational complexity of PDES are growing at an intractable rate. An active research topic is to build a surrogate-ready PDES framework where an accurate surrogate model built on machine learning can be used to forecast network traffic for improving PDES. In this paper, we make the first attempt to introduce two representative time series methods, the Autoregressive Integrated Moving Average (ARIMA) and the Adaptive Long Short-Term Memory (ADP-LSTM), to forecast the traffic in interconnect networks, using the Dragonfly system as a representative example. The proposed ADP-LSTM can efficiently adapt to the ever-changing network traffic, facilitating the forecasting capability for intricate network traffic, by incorporating a novel online learning strategy. Our preliminary analysis demonstrates promising results and shows that ADP-LSTM can consistently outperform ARIMA with significantly less time overhead.","PeriodicalId":246048,"journal":{"name":"Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125440115","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}

引用次数: 0

Reproducibility Report for the Paper: “Hybrid PDES Simulation of HPC Networks Using Zombie Packets” 论文的再现性报告:“使用僵尸包的HPC网络的混合PDES模拟”

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3596135

Wen Jun Tan

引用次数: 0

Hybrid Speculative Synchronisation for Parallel Discrete Event Simulation 并行离散事件模拟的混合推测同步

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591124

Andrea Piccione, Philipp Andelfinger, Alessandro Pellegrini

{"title":"Hybrid Speculative Synchronisation for Parallel Discrete Event Simulation","authors":"Andrea Piccione, Philipp Andelfinger, Alessandro Pellegrini","doi":"10.1145/3573900.3591124","DOIUrl":"https://doi.org/10.1145/3573900.3591124","url":null,"abstract":"Parallel discrete-event simulation (PDES) is a well-established family of methods to accelerate discrete-event simulations. However, the available algorithms vary substantially in the performance achievable for different models, largely preventing generic solutions applicable by modellers without expert knowledge. For instance, in Time Warp, the processing elements execute events asynchronously and speculatively with high aggressiveness, leading to frequent and costly rollbacks if misspeculations occur often. In contrast, synchronous approaches such as the new Window Racer algorithm exhibit a more cautious form of speculation. In the present paper, we combine these two fundamentally different algorithms within a single runtime environment, allowing for a choice of the best algorithm for different model segments. We describe the architecture and the algorithmic considerations to support the efficient coexistence and interaction of the algorithms without violating the correctness of the simulation. Our experiments using a synthetic benchmark and an epidemics model show that the hybrid algorithm is less sensitive to its configuration and can deliver substantially higher performance in models with varying degrees of coupling among entities compared to each algorithm on its own.","PeriodicalId":246048,"journal":{"name":"Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130448629","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}

引用次数: 2

HELICSAuto: Automating the Development of Cyber-Physical Co-Simulation Framework for Smart Grids HELICSAuto:智能电网网络物理联合仿真框架的自动化开发

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591118

Sayeb Mohammad Tadvin, Dong Jin, Hui Lin

引用次数: 0

A Study of Simulating Heterogeneous Workloads on Large-scale Interconnect Network 大规模互连网络异构工作负载模拟研究

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3593636

Xin Wang

引用次数: 0

Workload Interference Prevention with Intelligent Routing and Flexible Job Placement on Dragonfly 基于智能路径和灵活工作安排的蜻蜓负载干扰预防

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591119

Yao Kang, Xin Wang, Z. Lan

{"title":"Workload Interference Prevention with Intelligent Routing and Flexible Job Placement on Dragonfly","authors":"Yao Kang, Xin Wang, Z. Lan","doi":"10.1145/3573900.3591119","DOIUrl":"https://doi.org/10.1145/3573900.3591119","url":null,"abstract":"Dragonfly is an indispensable interconnect topology for exascale HPC systems. To link tens of thousands of compute nodes at a reasonable cost, Dragonfly shares network resources with the entire system such that network bandwidth is not exclusive to any single job. Since HPC systems are usually shared between multiple co-running workloads at the same time, network competition between co-existing workloads is inevitable. This network contention appears as workload interference, where a job’s network communication can be severely delayed by other jobs. Recent studies show that, compared with the deployed adaptive routing algorithms, an intelligent routing solution based on reinforcement learning named Q-adaptive routing can reduce workload interference. In addition to improving routing efficiency, job placement is a simple yet effective method to mitigate workload interference. In this study, we leverage the well-known parallel discrete event simulation toolkit, SST, to investigate workload interference on Dragonfly with three contributions. We first develop an automatic module that serves as the bridge between SST and HPC job scheduler for automatic simulation configuration and automated simulation launching. Next, we propose a flexible job placement strategy that can mitigate workload interference based on workload communication characteristics. Finally, we extensively examine the workload interference under various job placement and routing configurations.","PeriodicalId":246048,"journal":{"name":"Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130964876","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}

引用次数: 0

Effective Access to the Committed Global State in Speculative Parallel Discrete Event Simulation on Multi-core Machines 多核机推测并行离散事件仿真中承诺全局状态的有效存取

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591117

Romolo Marotta, Federica Montesano, F. Quaglia

{"title":"Effective Access to the Committed Global State in Speculative Parallel Discrete Event Simulation on Multi-core Machines","authors":"Romolo Marotta, Federica Montesano, F. Quaglia","doi":"10.1145/3573900.3591117","DOIUrl":"https://doi.org/10.1145/3573900.3591117","url":null,"abstract":"Output production and predicate detection are critical in speculative parallel discrete event simulation, since they need to take place accessing past state values—which have become committed—rather than the current state of the simulation objects, which is possibly affected by causality errors related to speculative event processing. In this article, we present an architecture that enables an effective management of the access to the committed state of any simulation object while still guaranteeing: (i) minimal impact on the forward execution of the simulation in terms of synchronization (and rollback generation) and (ii) highly balanced distribution of the tasks among all the threads running the simulation application. Our architecture is devised for speculative simulation engines running on top of shared-memory parallel machines, where worker threads full share the simulation workload. We exploit kernel-level facilities—targeting the Linux operating system—and user level ones, which work together for enabling a suited wall-clock-time collocation of the threads’ activities for the access to the committed global state of the simulation. We integrated our proposal within the USE (Ultimate Share-Everything) open-source simulation platform, and provide an experimental assessment of it.","PeriodicalId":246048,"journal":{"name":"Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121063130","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}

引用次数: 0

RCR Report of “Zero Lookahead? Zero Problem. The Window Racer Algorithm” “零展望?”的RCR报告零的问题。Window Racer算法”

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3596134

Romolo Marotta

引用次数: 0

Exploring Machine Learning Models with Spatial-Temporal Information for Interconnect Network Traffic Forecasting 基于时空信息的互联网络流量预测机器学习模型探索

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3593635

Xiongxiao Xu

引用次数: 0

Enhancing Fidelity of P4-Based Network Emulation with a Lightweight Virtual Time System 用轻量级虚拟时间系统增强p4网络仿真的保真度

Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Pub Date : 2023-06-21 DOI: 10.1145/3573900.3591120

Gong Chen, Zhexuan Hu, Dong Jin

{"title":"Enhancing Fidelity of P4-Based Network Emulation with a Lightweight Virtual Time System","authors":"Gong Chen, Zhexuan Hu, Dong Jin","doi":"10.1145/3573900.3591120","DOIUrl":"https://doi.org/10.1145/3573900.3591120","url":null,"abstract":"P4’s data-plane programmability allows for highly customizable and programmable packet processing, enabling rapid innovation in network applications, such as virtualization, security, load balancing, and traffic engineering. Researchers extensively use Mininet, a popular network emulator, integrated with BMv2, for fast and flexible prototyping of these P4-based applications, but due to its lower performance in terms of throughput and latency compared to a production-grade software switch like Open vSwitch, it is crucial to have an accurate and scalable emulation testbed. In this paper, we develop a lightweight virtual time system and integrate it into Mininet with BMv2 to enhance fidelity and scalability. By scaling the time of interactions between containers and the underlying physical machine by a time dilation factor (TDF), we can trade time with system resources, making the emulated P4 network appear to be faster from the viewpoint of the switch/host processes in the container. Our experimental results show that the testbed can accurately emulate much larger networks with high loads, scaled by a factor of TDF with extremely low system overhead.","PeriodicalId":246048,"journal":{"name":"Proceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116921770","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}

引用次数: 0