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ACM SIGSIM International Conference on Principles of Advanced discrete simulation (ACMSIGSIM-PADS)

作者： Cruz-Camacho, Elkin Brown, Kevin A. Wang, Xin Xu, Xiongxiao Shu, Kai Lan, Zhiling Ross, Robert B. Carothers, Christopher D. Rensselaer Polytech Inst Troy NY 12180 USA Argonne Natl Lab Lemont IL USA IIT Chicago IL 60616 USA

ISBN: (纸本)9798400700309

High-fidelity network simulations provide insights into new realms for high-performance computing (HPC) architectures, although at a high cost. Surrogate models offer a significant reduction in runtime, yet they cannot serve as complete replacements and should be only used when appropriate. Thus the need for hybrid modeling, where high-fidelity simulation and surrogates run side-by-side. We present a surrogate model for HPC networks in which packets bypass the network, and the network state itself is suspended when switching to the surrogate. To bypass the network, every packet is scheduled to arrive at a predicted time in the future estimated from historical data;to suspend the network, all in-flight packets are delivered to their destinations, but they are kept in the system to awaken as zombies when switching back to high-fidelity. Speedup for a hybrid model is relative to the proportion of surrogate to high-fidelity. We obtained a 3x speedup for a simulation where 70% of virtual time was spent in surrogate mode. When considering the surrogate portion only, the speedup jumps to nearly 20x on a uniform random network traffic example. The accuracy of the overall simulation increased when the network state was suspended instead of ignored, which demonstrates the need for modeling the network state when transitioning from surrogate back to high-fidelity mode.

关键词： parallel discrete-event simulation HPC networks Surrogate simulation

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A Visual Analytics Framework for Analyzing parallel and Distributed Computing Applications

A Visual Analytics Framework for Analyzing Parallel and Dist...

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IEEE Conference on Visualization in Data Science (VDS)

作者： Li, Jianping Kelvin Fujiwara, Takanori Kesavan, Suraj P. Ross, Caitlin Mubarak, Misbah Carothers, Christopher D. Ross, Robert B. Ma, Kwan-Liu Univ Calif Davis Davis CA 95616 USA Rensselaer Polytech Inst Troy NY 12181 USA Argonne Natl Lab 9700 S Cass Ave Argonne IL 60439 USA

ISBN: (纸本)9781728150475

To optimize the performance and efficiency of HPC applications, programmers and analysts often need to collect various performance metrics for each computer at different time points as well as the communication data between the computers. This results in a complex dataset that consists of multivariate time-series and communication network data, which makes debugging and performance tuning of I IPC applications challenging. Automated analytical methods based on statistical analysis and unsupervised learning are often insufficient to support such tasks without the background knowledge from the application programmers. To better explore and analyze a wide spectrum of HPC datasets, effective visual data analytics techniques are needed. In this paper, we present a visual analytics framework for analyzing HPC datasets produced by parallel discrete-event simulations (PDES). Our framework leverages automated time-series analysis methods and effective visualizations to analyze both multivariate time-series and communication network data. Through several case studies for analyzing the performance of PDES, we show that our visual analytics techniques and system can be effective in reasoning multiple performance metrics, temporal behaviors of the simulation, and the communication patterns.

关键词： Visual analytics information visualization time-series data multivariate data performance analysis parallel discrete-event simulation

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Exposing Inter-process Information for Efficient PDES of Spatial Stochastic Systems on Multicores

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ACM TRANSACTIONS ON MODELING AND COMPUTER simulation 2019年第2期29卷 11-11页

作者： Linden, Jonatan Bauer, Pavol Engblom, Stefan Jonsson, Bengt Uppsala Univ Dept Informat Technol Uppsala Sweden German Ctr Neurodegenerat Dis Neural Networks Bonn Germany

We present a new approach for efficient process synchronization in parallel discrete event simulation on multicore computers. We aim specifically at simulation of spatially extended stochastic system models where time intervals between successive inter-process events are highly variable and without lower bounds: This includes models governed by the mesoscopic Reaction-Diffusion Master Equation (RDME). A central part of our approach is a mechanism for optimism control, in which each process disseminates accurate information about timestamps of its future outgoing interprocess events to its neighbours. This information gives each process a precise basis for deciding when to pause local processing to reduce the risk of expensive rollbacks caused by future "delayed" incoming events. We apply our approach to a natural parallelization of the Next Subvolume Method (NSM) for simulating systems obeying RDME. Since this natural parallelization does not expose accurate timestamps of future interprocess events, we restructure it to expose such information, resulting in a simulation algorithm called Refined parallel NSM (Refined PNSM). We have implemented Refined PNSM in a parallel simulator for spatial extended Markovian processes. On 32 cores, it achieves an efficiency ranging between 43-95% for large models, and on average 37% for small models, compared to an efficient sequential simulation without any code for parallelization. It is shown that the gain of restructuring the naive parallelization into Refined PNSM more than outweighs its overhead. We also show that our resulting simulator is superior in performance to existing simulators on multicores for comparable models.

关键词： parallel discrete-event simulation PDES optimism control multicore spatial stochastic simulation

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A Visual Analytics Framework for Analyzing parallel and Distributed Computing Applications

A Visual Analytics Framework for Analyzing Parallel and Dist...

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IEEE Visualization in Data Science (VDS)

作者： Jianping Kelvin Li Takanori Fujiwara Suraj P. Kesavan Caitlin Ross Misbah Mubarak Christopher D. Carothers Robert B. Ross Kwan-Liu Ma University of California Davis Rensselaer Polytechnic Institute Argonne National Laboratory

ISBN: (纸本)9781728150482

To optimize the performance and efficiency of HPC applications, programmers and analysts often need to collect various performance metrics for each computer at different time points as well as the communication data between the computers. This results in a complex dataset that consists of multivariate time-series and communication network data, which makes debugging and performance tuning of HPC applications challenging. Automated analytical methods based on statistical analysis and unsupervised learning are often insufficient to support such tasks without the background knowledge from the application programmers. To better explore and analyze a wide spectrum of HPC datasets, effective visual data analytics techniques are needed. In this paper, we present a visual analytics framework for analyzing HPC datasets produced by parallel discrete-event simulations (PDES). Our framework leverages automated time-series analysis methods and effective visualizations to analyze both multivariate time-series and communication network data. Through several case studies for analyzing the performance of PDES, we show that our visual analytics techniques and system can be effective in reasoning multiple performance metrics, temporal behaviors of the simulation, and the communication patterns.

关键词： Visual analytics information visualization time-series data multivariate data performance analysis parallel discrete-event simulation Visual analytics information visualization time series data Performance metrics discrete event simulation diethylstilbestrol monophosphate High Performance Computing

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Fine-Grained Local Dynamic Load Balancing in PDES 18

Fine-Grained Local Dynamic Load Balancing in PDES

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32nd ACM SIGSIM Conference on Principles of Advanced discrete simulation (SIGSIM-PADS)

作者： Linden, Jonatan Bauer, Pavol Engblom, Stefan Jonsson, Bengt Uppsala Univ Dept Informat Technol Uppsala Sweden

ISBN: (纸本)9781450350921

We present a fine-grained load migration protocol intended for parallel discrete event simulation (PDES) of spatially extended models. Typical models have domains that are fine-grained discretizations of some volume, e.g., a cell, using an irregular three-dimensional mesh, where most events span several voxels. Phenomena of interest in, e.g., cellular biology, are often non-homogeneous and migrate over the simulated domain, making load balancing a crucial part of a successful PDES. Our load migration protocol is local in the sense that it involves only those processors that exchange workload, and does not affect the running parallel simulation. We present a detailed description of the protocol and a thorough proof for its correctness. We combine our protocol with a strategy for deciding when and what load to migrate, which optimizes both for load balancing and inter-processor communication using tunable parameters. Our evaluation shows that the overhead of the load migration protocol is negligible, and that it significantly reduces the number of rollbacks caused by load imbalance. On the other hand, the implementation mechanisms that we added to support fine-grained load balancing incur a significant cost.

关键词： parallel discrete-event simulation PDES Load Balancing Load Migration Load Metric

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Improving accuracy and performance through automatic model generation for gate-level circuit PDES with reverse computation 15

Improving accuracy and performance through automatic model g...

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3rd ACM Conference on SIGSIM-Principles of Advanced discrete simulation, SIGSIM-PADS 2015

作者： Gonsiorowski, Elsa LaPre, Justin M. Carothers, Christopher D. Rensselaer Polytechnic Institute TroyNY United States

ISBN: (纸本)9781450335836

Gate-level circuit simulation is an important step in the design and validation of complex circuits. This step of the process relies on existing libraries for gate specifications. We start with a generic gate model for Rensselaer's Optimistic simulation System (ROSS), a parallel discrete-event simulation framework. This generic model encompasses all functionality needed by optimistic simulation using reverse computation. We then describe a parser system which uses a standardized gate library to create a specific model for simulation. The generated model is comprised of several functions including those needed for an accurate model of timing behavior. To quantify the improvements that an automatically generated model can have over a hand written model we compare two gate library models: an automatically generated LSI-10K library model and a previously investigated, handwritten, simplified GTECH library model [19]. We conclude that the automatically generated model is a more accurate model of actual hardware. The generated model also represents the timing behavior with an approximately 50 times higher degree of fidelity. In comparison to previous results, we find that the automatically generated model is able to achieve better optimistic simulation performance when measured against conservative simulation. We identify peak optimistic performance when using 128 MPI-Ranks on eight nodes of an IBM Blue Gene/Q machine. © 2015 ACM.

关键词： parallel discrete-event simulation digital logic simulation automatic logic generation design automation

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A Case Study in Using Massively parallel simulation for Extreme-Scale Torus Network Codesign 14

A Case Study in Using Massively Parallel Simulation for Extr...

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2nd ACM Conference on SIGSIM Principles of Advanced discrete simulation (ACM SIGSIM/PADS)

作者： Mubarak, Misbah Carothers, Christopher D. Ross, Robert B. Carns, Philip Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA Argonne Natl Lab Math & Comp Sci Div Chicago IL 60439 USA

ISBN: (纸本)9781450327947

A high-bandwidth, low-latency interconnect will be a critical component of future exascale systems. The torus network topology, which uses multidimensional network links to improve path diversity and exploit locality between nodes, is a potential candidate for exascale interconnects. The communication behavior of large-scale scientific applications running on future exascale networks is particularly important and analytical/algorithmic models alone cannot deduce it. Therefore, before building systems, it is important to explore the design space and performance of candidate exascale interconnects by using simulation. We improve upon previous work in this area and present a methodology for modeling and simulating a high-fidelity, validated, and scalable torus network topology at a packet-chunk level detail using the Rensselaer Optimistic simulation System (ROSS). We execute various configurations of a 1.3 million node torus network model in order to examine the effect of torus dimensionality on network performance with relevant HPC traffic patterns. To the best of our knowledge, these are the largest torus network simulations that are carried out at such a detailed fidelity. In terms of simulation performance, a 1.3 million node, 9-D torus network model is shown to process a simulated exascale-class workload of nearest-neighbor traffic with 100 million message injections per second per node using 65,536 Blue Gene/Q cores in a simulation run-time of only 25 seconds. We also demonstrate that massive-scale simulations are a critical tool in exascale system design since small-scale torus simulations are not always indicative of the network behavior at an exascale size. The take-away message from this case study is that massively parallel simulation is a key enabler for effective extreme-scale network codesign.

关键词： High-performance computing parallel discrete-event simulation Massively parallel architectures Torus networks Exascale systems

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Optimal Run Length for discrete-event Distributed Cluster-Based simulations

Optimal Run Length for Discrete-Event Distributed Cluster-Ba...

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14th Annual International Conference on Computational Science

作者： Borges, Francisco Gutierrez-Milla, Albert Suppi, Remo Luque, Emilio Univ Autonoma Barcelona Dept Comp Architecture & Operating Syst E-08193 Barcelona Spain

In scientific simulations the results generated usually come from a stochastic process. New solutions with the aim of improving these simulations have been proposed, but the problem is how to compare these solutions since the results are not deterministic. Consequently how to guarantee that the output results are statistically trusted. In this work we apply a statistical approach in order to define the transient and steady state in discrete event distributed simulation. We used linear regression and batch method to find the optimal simulation size. As contributions of our work we can enumerate: we have applied and adapted the simple statistical approach in order to define the optimal simulation length;we propose the approximate approach to normal distribution instead of generate replications sufficiently large;and the method can be used in other kind of non-terminating science simulations where the data either have a normal distribution or can be approximated by a normal distribution.

关键词： parallel and distributed simulation parallel discrete-event simulation High performance distributed simulation Output analysis Run length Transient state Steady state

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A unifying framework for specifying DEVS parallel and distributed simulation architectures

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simulation-TRANSACTIONS OF THE SOCIETY FOR MODELING AND simulation INTERNATIONAL 2013年第11期89卷 1293-1309页

作者： Adegoke, Adedoyin Togo, Hamidou Traore, Mamadou K. African Univ Sci & Technol Galadimawa Abuja Nigeria Univ Sci Tech & Technol Bamako Bamako Mali Univ Blaise Pascal LIMOS Aubiere France

DEVS (discrete event System Specification) is an approach in the area of modeling and simulation that provides a means of specifying dynamic systems. A variety of DEVS tools have been implemented without a standard developmental guideline across the board, consequently revealing a lack of central frameworks for integrating heterogeneous DEVS simulators. When implementing a DEVS Simulator there are salient concepts that are intuitively defined, such as how events should be processed, what simulation architecture to use, what existing procedures (set of rules/algorithm) can be used, what should be the organizational architecture and so on. The aim of this paper is to propose a theoretical guide in building a DEVS distributed simulation as well as a formalization of underlying concepts to allow symbolic reasoning and automated code synthesis. From a review of existing implementation approaches, we propose a taxonomy of the identified concepts, including some formal definitions as they constitute the essential building blocks of performing parallel discrete-event simulation by utilizing DEVS. The contribution of this taxonomy and its impact as a unifying framework is that it provides a more systematic understanding of the process of constructing a DEVS simulator. Also, it offers an abstract way for integrating different and heterogeneous DEVS implementation strategies and thus can serve as a contribution to the on-going DEVS standardization efforts.

关键词： DEVS parallel discrete-event simulation conceptual framework simulation Tree simulation Graph

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Optimal Run Length for discrete-event Distributed Cluster-based simulations

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Procedia Computer Science 2014年 29卷 73-83页

作者： Francisco Borges Albert Gutierrez-Milla Remo Suppi Emilio Luque Department of Computer Architecture & Operating Systems Universitat Autonoma de Barcelona Bellaterra08193 Barcelona Spain

In scientific simulations the results generated usually come from a stochastic process. New solutions with the aim of improving these simulations have been proposed, but the problem is how to compare these solutions since the results are not deterministic. Consequently how to guarantee that the output results are statistically trusted. In this work we apply a statistical approach in order to define the transient and steady state in discrete event distributed simulation. We used linear regression and batch method to find the optimal simulation size. As contributions of our work we can enumerate: we have applied and adapted the simple statistical approach in order to define the optimal simulation length; we propose the approximate approach to normal distribution instead of generate replications sufficiently large; and the method can be used in other kind of non-terminating science simulations where the data either have a normal distribution or can be approximated by a normal distribution.

关键词： parallel and distributed simulation parallel discrete-event simulation High performance distributed simulation Output analysis Run length Transient state Steady state

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