Discrete | Kalyan Perumalla

DarkNet Cyber Resilience

Tue, 22 Mar 2022 00:00:00 +0000

DarkNet Cyber Resilience investigates the impacts of cyber stress and its thresholds of impact on alternative timing signals for the US national energy grid.

Cyber Resilience of Alternative Timing for Energy Grids

Overview

This project is focused on performing a systematic evaluation of the impacts of cyber stress on the system. It is developing tools that enable early detection of performance issues and rapid recovery from cyber-related events. A unique advancement of the project lies in going beyond general cybersecurity vulnerabilities and exposures (CVE). This is achieved by evaluating their implications to the cyber resilience specifically with regard to precise effects on the transmission and receipt of timing signals over the complex networks connecting the timing sources to the geographically-distant subscribers.

Key Links

DarkNet Website

Gallery

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program: DarkNet
Prime: Oak Ridge National Laboratory (ORNL)

Selected Publications

DarkNet Cyber Resilience

Two key cyber elements affecting the grid’s timing capability are Cyber Resilience and Cyber Trust. The timing services of DarkNet are systematically subjected to a range of cyber phenomena that stress four key performance factors, namely: Accuracy, Manageability, Telemetry, and Visibility. This analysis is designed to provide insights into four important categories of undesirable cyber phenomena: Loss of View (LoV), Loss of Control (LoC), Manipulation of View (MoV), and Manipulation of Control (MoC).

Kalyan Perumalla, Juan Lopez

PDF

NAERM

Sat, 01 Jan 2022 00:00:00 +0000

North American Energy Resilience Model provides the next generation planning infrastructure for the US national energy grid using a cloud-based real-time, interoperable, and federated modeling, simulation, and visualization technology.

Overview

NAERM dependencies across energy infrastructure layers

Interactive Contingency Selection

Contributions

As ORNL lead for the NAERM Software Architecture Group, my efforts were focused on enabling cloud-based federated simulations executing in a distributed fashion across PNNL, ORNL and ANL servers. In particular, a dynamically configured and launched network of virtual machines via Amazon Web Services (AWS), coordinated using AWS Step Functions. Automated launches of electric transmission grid scenarios can be triggered in a highly responsive fashion. The software architecture was designed to evaluated using the Siemens PSS/E simulator instances that were licensed to execute in on-premise mode only at ORNL. Additionally, PowerWorld simulations were dynamically interoperated with other instances using federated simulation interfaces of the HELICS system for interfacing with gas network outage models simulated at ANL.

A contingency visualization, selection and launch tool was developed with one of my team members (Dr. Maksudul Alam).

Architecture

Cloud-based Software Architecture for Federated Simulation

Demo Videos

Description

The NAERM will ultimately provide real-time situational awareness and analysis capabilities for emergency events for optimal operations and recovery, so that the Federal Government can quickly and effectively prepare and respond, for example, providing recommendations in coordination with State and local governments, Federal Emergency Management Agency (FEMA), and the National Guard. While the primary focus is on the energy sector, the NAERM will further assist industry in assessing the resilience implications of energy planning decisions on associated infrastructure. NAERM capabilities will also be leveraged by DOE’s National Nuclear Security Administration (NNSA), the Department of Defense (DoD), and the Department of Homeland Security (DHS) in support of their national security missions.
– NAERM Report

The North American Energy Resilience Model project is focused on developing the next generation planning infrastructure for the US national energy grid using a cloud-based real-time, interoperable, and federated modeling, simulation, and visualization technology

Ultimately, NAERM will enable DOE’s provision of situational assessment advice to industry and government to ameliorate the risk of and consequence associated with large- scale service disruptions across infrastructure sectors—and geographic and organizational boundaries—and the lengthy restoration and recovery operations following an extreme event. The NAERM will advance the state-of-science in planning and operations of energy supply in extreme events and provide rigorous resilience and associated economics metrics for these sectors.
– NAERM Report

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program: North American Energy Resilience Model (NAERM)
Team: ORNL, PNNL, LLNL, ANL, and others

ZeroIn

Sat, 01 Jan 2022 00:00:00 +0000

Our formulation of a new AI/ML-based, real-time computational framework aims to learn and flag defects in software as early as the time of commit in the developers’ repositories.

ZeroIn Network

Overview

Using novel AI/ML techniques, ZeroIn zeroes-in onto problems in software repositories and aims to identify code vulnerabilities at their very origin, namely, at the time at which developers commit their codes into their repositories.

ZeroIn: Characterizing the Data Distributions of Commits in Software Repositories

A characterization of the software development metadata is presented in terms of distributions of data that best captures the trends in the datasets, to feed into the machine learning components of ZeroIn to exploit connectivity among the sets of repositories, commits, and developers.

Kalyan Perumalla, Aradhana Soni, Rupam Dey, Steven Rich

PDF

Using Machine Learning Towards Early Flagging of Potentially Buggy Software Commits

Using multiple classifiers we verify the feasibility of using metadata from synthetic datasets modeled by a characterization of a few large software repositories and developer profiles. Results show that the metadata-based learning approach appears promising towards early flagging of potentially buggy commits in software repositories.

Aradhana Soni, Kalyan Perumalla

PDF

Characterizing the Distributions of Commits in Large Source Code Repositories

We present preliminary results from characterizing the distribution of 452 million commits in a metadata listing from GitHub repositories. Based on multiple distributions, we find the best fits and second best fits across different ranges in the data. The characterization is aimed at synthetic repository generation suitable for use in simulation and machine learning.

Aradhana Soni, Kalyan Perumalla, Rupam Dey

PDF

Organization

Sponsor: Industry
Institutions: University of Tennessee, Knoxville
Period: 2021-2024

Gallery

DES Grid

Sat, 01 Jan 2022 00:00:00 +0000

Discrete Event Modeling of the Electric Grid is a new non-equilibrium, transient analysis model and solver that is indispensable for new advancements in grids with high renewable penetration.

Novel Discrete Event Modeling and Simulation of Energy Grids

Overview

This project is aimed at creating and demonstrating a new approach to transient analysis for power systems that has three key advantages over existing methods. These advantages are:

an accurate, physically plausible model that creates signals perceived by sensors throughout the transmission and distribution networks;
enabling a natural and accurate representation of modern electrical loads, such as power electronics devices, within the distribution system, and
a computationally tractable method of simulating these models at large scales.

Gallery

Approach

Grid modeling and simulation requires accurate capture of physics combined with internal and external behavioral elements. The physics includes movement of electricity at multiple scales broadly classified as transmission, distribution, and sub-distribution. This is driven by internal behaviors: generation is dictated by physics of power generators plus sophisticated controls to maintain voltage, and by consumption loads driven by a wide variety of traditional energy sinks as well as increasingly sophisticated sensors and controllers introduced by smart grid technologies. In light of advances in distributed energy resources and renewables, most aspects of transport, generation, consumption and responses are also greatly controlled by rich internal behaviors. Our approach provides support in one form or another to modeling and simulating all the aforementioned grid elements.

We approach the grid modeling and simulation problem with a first principles-based, fully generalized, transient simulation view of the grid. Our starting point is that of a new three-phase model that is equally applicable at multiple levels, spanning transmission, distribution and sub-distribution.

Our three-phase model is designed to produce voltage and current wave forms at scales in time and geographical spaces sufficient to understand system-wide dynamics resulting from localized-yet-interconnected behaviors of:

signal processing algorithms and logic in inverters, protection devices, and other equipment that act on millisecond time scales;
electrical and mechanical dynamics of conventional and new solar, fossil fuel, nuclear, and other power generators that evolve over tens of seconds; and
detailed dynamics of loads that may contribute to large-scale distributed controls that counterbalance the volatility of distributed/renewable generation.

We create a new type of power system model that integrates dynamic load and generation models with a dynamic, rather than quasi-equilibrium, model of the transmission and distribution network. This new model enables relevant, simulation-based performance assessments of new sensors, such as next generation phasor measurement units and distribution-based frequency sensors, and provide an unprecedented, indispensable understanding of how sensor characteristics impact wide area control strategies.

The new model developed through this research replaces pseudo equilibrium models of transmissions and loads with dynamic elements that properly resolve the physics that transmit electrical power. With these new models it becomes possible in simulation to measure physically plausible voltage signals throughout a large power system during a transient, and to do so with complete knowledge of the events within the modeled power system that produced the observed signal. This new insight will propel advancing sensing and control technologies that would be infeasible to engineer with present, inadequate models and experimental test beds.

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program:
  - Grid Modernization Laboratory Consortium (GMLC)
  - Advanced Grid Modeling (AGM)
Prime: Oak Ridge National Laboratory (ORNL)

Additional Motivation

Current methods for electromechanical transient analysis of electrical power systems predate the significant, recent advances in sensing technology that allow measurements of frequency to be made through the transmission and distribution systems. Consequently, current methods of analysis make no attempt to accurately calculate the signals that these sensors are designed to monitor. This creates considerable difficulties when current methods, models, and simulation tools are used to assess how a new device that relies on measures of frequency will affect the response of the power system to a disturbance,

This problem has been widely recognized in recent years, and numerous, essentially ad hoc, solutions have been proposed. While these ad hoc techniques can, and have, been easily integrated into existing tools, they generally lack a fundamental basis in the physics of an electrical power system, are prone to large numerical errors, or both. At best, these proposals must be viewed as a stop gap measure until models become available that properly resolve dynamical effects in the transmission network that, in conjunction with the generator dynamics, ultimately determine how a signal is perceived by a sensor within the transmission and distribution systems.

Selected Publications

A Case Study in Simulation Methods for Power Electronic Circuits

A simplified circuit is used as a case study to uncover and highlight key considerations in the use of traditional numerical simulation methods and compare them with those obtained from alternative methods that are discrete event-based from the outset. Results show the regimes where the traditional numerical methods and the alternative discrete event methods are applicable, and the need for discrete event approaches that precisely and efficiently resolve switching dynamics produced by power electronics systems that are important in emerging grid scenarios, such as large scale renewable energy.

James Nutaro, Suman Debnath, Kalyan Perumalla

PDF Cite DOI

Digital Twin Framework

Sat, 01 Jan 2022 00:00:00 +0000

Our novel Digital Twin Framework (DTF) is designed to improve resilience of critical infrastructure systems by continuously comparing the infrastructure state with automatically generated, AI/ML-based, real-time digital-twin simulation of the system.

Team

Digital Twin Framework Software Architecture

Overview

As the level of automation in critical infrastructure increases, the ability to detect cyber intrusions becomes more crucial and extremely challenging. Recent cyber attacks demonstrate the devastating and widespread affects they can have on critical infrastructure.

DTF is designed specifically to detect and eventually prevent such attacks, with models validated against experimental data from two critical infrastructure experimental emulators – a canal lock system and an electric distribution system – exhibiting very different dynamics. The canal lock system’s digital twin uses a recurrent neural network trained from the experimental data collected via the DTF. A digital twin of the transmission system is created using a commercial real-time power systems simulator and integrated into our DTF along with the hardware, embedded controllers, and live sensor data using the Open Field Message Bus data model, and publish/subscribe communication protocols. A cyber attack is used on both systems to demonstrate the DTF’s detection capability.

Organization

Sponsor: Lab Directed Research and Development, Oak Ridge National Laboratory
Period: 2018-2020

Gallery

On the Effectiveness of Recurrent Neural Networks for Live Modeling of Cyber-Physical Systems

We empirically study the effectiveness of Recurrent Neural Network (RNN)-based models as the basis of DT-based resilience and uncover the important characteristics of an RNN-based solution with experimentation on a lab-scale Canal Lock CPS emulator with live validations and attack scenarios. For the first time, we demonstrate actual, real-time use of a RNN-based model as a DT for performing live analysis on an operational CPS.

Srikanth Yoginath, Varisara Tansakul, Supriya Chinthavali, Curtis Taylor, Joshua Hambrick, Philip Irminger, Kalyan Perumalla

PDF Cite DOI

A Digital Twin Framework for Testing, Evaluation and Deployment of Resilient Cyber-physical Systems

We describe an approach to detecting and preventing cyber attacks by continuously comparing the infrastructure state with a real-time digital-twin simulation of it. Specifically, we describe and demonstrate a Digital Twin Framework (DTF) designed specifically to detect and eventually prevent such attacks. The canal lock system’s digital twin uses a recurrent neural network trained from the experimental data collected via the DTF.

Raymond Hink, Mark Buckner, Supriya Chinthavali, Chris Craig, Timothy Daniel, Joel Dawson, Milton Ericson, Joshua Hambrick, Philip Irminger, Ryan Kerekes, Juan Lopez, Kalyan Perumalla, Nicholas Peters, Stacy Prowell, Varisara Tansakul, Curtis Taylor, Bailu Xiao, Srikanth Yoginath

PDF

EpiClone: Epidemiological Clonable Simulations

Sat, 01 Jan 2022 00:00:00 +0000

Cloned simulations of epidemiological outbreaks like COVID-19 can now rapidly evaluate millions of what-if scenarios at national and world scales, and efficiently exploit 1000s of GPUs.

EpiClone model elements

EpiClone simulating USA scenarios

Overview

EpiClone represents the next advancements in what-if decision evaluation on state-of-the-art accelerated computing platforms including supercomputers containing thousands of GPUs.

EpiClone addresses global epidemiological outbreaks via an incremental simulation-based what-if decision tree evolution. EpiClone offers new scaling capabilities that were previously not possible before for rapidly simulating thousands or millions of epidemiological scenarios.

The EpiClone approach and results in scalable modeling and fast scenario exploration provide a leap in the analyses of epidemics and other complex systems.

Gallery

Organization

Sponsor: Lab Directed Research and Development, Oak Ridge National Laboratory
Period: 2015-2017

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. We present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning.

Srikanth Yoginath, Kalyan Perumalla

PDF Cite DOI

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What–If Analyses of Localized and Dynamic Effects

A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

Kalyan Perumalla, Maksudul Alam

PDF Cite DOI

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects a…

Kalyan Perumalla, Sudip Seal

PDF Cite

Reversible Parallel Discrete-Event Execution of Large-scale Epidemic Outbreak Models

The spatial scale, runtime speed, and behavioral detail of epidemic outbreak simulations altogether …

Kalyan Perumalla, Sudip Seal

PDF Cite Slides

Network Simulation

Sat, 01 Jan 2022 00:00:00 +0000

ISBN 978-1439873403 | Morgan & Claypool | Amazon
This book covers all concepts in modeling and simulating wired and wireless computer networks using parallel computing to reach Internet-scale simulations.

Overview

Network Simulation

A detailed introduction to the design, implementation, and use of network simulation tools is presented. The requirements and issues faced in the design of simulators for wired and wireless networks are discussed. Abstractions such as packet- and fluid-level network models are covered. Several existing simulations are given as examples, with details and rationales regarding design decisions presented. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the scale and performance of a simulation environment. Finally, a case study of two simulation tools is presented that have been developed using distributed simulation techniques. This text is essential to any student, researcher, or network architect desiring a detailed understanding of how network simulation tools are designed, implemented, and used.

Reference

Network Simulation

A detailed introduction to the design, implementation, and use of network simulation tools is presen…

Richard Fujimoto, Kalyan Perumalla, George Riley

PDF Cite

CloneX

Sat, 01 Jan 2022 00:00:00 +0000

Cloned eXecution of simulations is a powerful decision-making system to incrementally evaluate millions of what-if scenarios and scale to 1000s of GPUs.

Illustration of CloneX what-if tree on diffusion processes

CloneX computational and memory savings with increasing tree depth

Overview

CloneX is a novel system we designed for scalable simulation cloning, consisting of a conceptual simulation framework, algorithmic foundations, and a highly scalable runtime interface. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a large parallel system without full physical duplication of computation and memory.

CloneX Software Architecture

Titan Supercomputer with 1000s of GPUs

CloneX efficiently simulates a tree of multiple what-if scenarios unraveled during the course of a normal (base) simulation. Cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree.

CloneX has been tested on 1000s of GPUs of a supercomputing system and evaluated with multiple benchmarks – such as heat diffusion, forest fire, and disease propagation models – delivering a speed up of over two orders of magnitude compared to replicated runs.

CloneX represents a major leap in ensemble simulations as a significantly faster and scalable way to execute many what-if scenarios of large simulations.

Organization

Sponsors: US Department of Energy (DOE)
- Office: Advanced Scientific Computing Research (ASCR)
  - Program: Early Career Research Program (ECRP)
- Office: ORNL Strategic Planning Office
  - Program: Laboratory-Directed Research and Develoopment (LDRD)
Period: 2015-2017

Gallery

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What–If Analyses of Localized and Dynamic Effects

Kalyan Perumalla, Maksudul Alam

PDF Cite DOI

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Srikanth Yoginath, Kalyan Perumalla

PDF Cite DOI

HELICS

Sat, 01 Jan 2022 00:00:00 +0000

Hierarchical Engine for Large-Scale Infrastructure Co-Simulation (HELICS) is the first open-source software platform that co-simulates the nation’s power grid across transmission, distribution, and data communication systems.

Hierarchical Engine for Large-Scale Infrastructure Co-Simulation (HELICS)

Overview

HELICS enables grid planners and operators to understand how to navigate challenges such as integrating large-scale renewable energy resources and digital devices and defending against natural disasters and cyber threats.

HELICS was nominated to the R&D100 awards and was selected as an R&D100 Award finalist in 2018.

R&D100 Finalist Award for HELICS

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program: Grid Modernization Laboratory Consortium (GMLC)
Period: 2015-2017
Team: ORNL, PNNL, LLNL, ANL, and others

NetWarp

Sat, 01 Jan 2022 00:00:00 +0000

NetWarp is a novel time-synchronized virtual machine(VM)-based parallel simulation framework that accurately lifts the devices and the network communications to a virtual time plane while retaining full fidelity.

NetWarp

Organization

Sponsors: US Department of Defense
- Office: Army Research Laboratory (ARL)
- Office: Missile Defense Agency (MDA)
- Programs: Computational Sciences, STTR
Prime: Oak Ridge National Laboratory (ORNL)

Gallery

summary: Secure Virtual Environment for Cyber Resiliency Validation building on NetWarp technology for cybersecurity in hardware and software of missile defense systems

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in defense communications, …

Srikanth Yoginath, Kalyan Perumalla, Brian Henz

PDF Cite DOI

Taming Wild Horses: The Need for Virtual Time-based Scheduling of VMs in Network Simulations

The next generation of scalable network simulators employ virtual machines (VMs) to act as high-fidelity models of traffic producer/consumer nodes…

Srikanth Yoginath, Kalyan Perumalla, Brian Henz

PDF Cite

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES)…

Srikanth Yoginath, Kalyan Perumalla

PDF Cite

Rocks3D-HPC

Sat, 01 Jan 2022 00:00:00 +0000

Rocks3D-HPC is an efficient parallelization of the Rocks3D high-fidelity earth moving equipment simulation based on the Discrete Element Method implemented using FORTRAN, OpenMP multi-threading, and message passing interface (MPI) for high performance computing.

Organization

Sponsor: Caterpillar, Inc.
Institutions: ORNL

Gallery

RealSim: Real-Time Simulations

Sat, 01 Jan 2022 00:00:00 +0000

Real-time Simulations is a simulation framework for fast evaluation of national emergency scenarios such as hurricanes, evaluated with large data streams and real-time computation on the latest hardware platforms on the edge.

RealSim

Gallery

Organization

Sponsor: Department of Homeland Security (DHS)
Period: 2006-2009

Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulati…

Kalyan Perumalla, Brandon Aaby, Srikanth Yoginath, Sudip Seal

Cite

Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulati…

Kalyan Perumalla, Brandon Aaby, Srikanth Yoginath, Sudip Seal

PDF Cite Slides

An Analysis Approach to Large-Scale Vehicular Network Simulations

[Pub 28]

Kalyan Perumalla, Martin Beckerman

PDF Cite

On Accounting for the Interplay of Kinetic and Non-Kinetic Aspects of Population Mobility Models

[Pub 31]

Kalyan Perumalla

PDF Cite

Efficient Simulation of Agent-Based Models on Multi-GPU and Multi-Core Clusters

An effective latency-hiding mechanism is presented in the parallelization of agent-based model simul…

Brandon Aaby, Kalyan Perumalla, Sudip Seal

PDF Cite Slides

Computational Spectrum of Agent Model Simulation

The study of human social behavioral systems is finding renewed interest in military, homeland secur…

Kalyan Perumalla

Cite

A Connectionist Modeling Approach to Rapid Analysis of Emergent Social Cognition Properties in Large-Populations

Traditional modeling methodologies, such as those based on rule-based agent modeling, are exhibiting…

Kalyan Perumalla, Jack C. Schryver

PDF Cite Slides

Data Parallel Execution Challenges and Runtime Performance of Agent Simulations on GPUs

[Pub 27]

Kalyan Perumalla, Brandon Aaby

PDF Cite

A Case Study of Efficient Social Network Simulation through General Processing on Graphics Processing Units (GPGPUs)

Agent based simulation has been both a large area of study and a widely used tool for scientific research in past years…

Brandon Aaby, Kalyan Perumalla

Cite

Exploratory Research for Extreme-Scale Science (EXPRESS)

Mon, 01 Jan 2024 00:00:00 +0000

Awards

Solicitation PDF

Original at OSTI
Cached local copy

Selected Pages

Selected Extracts

Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, visualization, and artificial intelligence on increasingly heterogeneous architectures. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.

Exploratory Research for Extreme-Scale Science (EXPRESS) opportunities exist for the following research topics:

A. Harnessing Technology Innovations to Accelerate Science through Visualization
B. Scalable Space-Time Memories for Large Discrete/Agent-Based Models
C. Neuromorphic Computing
D. Advanced Wireless
E. Quantum Hardware Emulation

Applications submitted in response to this FOA must substantially address one among the preceding list of research topics.

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Wed, 11 May 2022 00:00:00 +0000

https://www.osti.gov/servlets/purl/1855247

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What–If Analyses of Localized and Dynamic Effects

Sun, 01 Aug 2021 00:00:00 +0000

https://link.springer.com/article/10.1007/s41745-021-00253-1

A Case Study in Simulation Methods for Power Electronic Circuits

Mon, 19 Jul 2021 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/9552085

COVID-relevant Scalable Computational Research Directions and Tools

Thu, 09 Apr 2020 00:00:00 +0000

This seminar conveys some directions and technical ideas being pursued by the Discrete Computing Systems Group of the Computer Science and Mathematics Division, in collaboration with others at the lab. Some of the scalable computational tools ready for applying to challenging computational problems are presented. Actual working codes ready for customization to COVID-related efforts are described, which are built for scaling to supercomputing platforms such as Summit.

Topics that are covered include:

A high resolution simulator, ExaCorona, that scales from laptops to leadership class supercomputers, is outlined that uses a discrete event model of virus spread, with probabilistically timed state transitions at the individual level across millions of individuals represented with arbitray geography and mobility characteristics.
A clonable simulation framework, CloneX, is introduced that enables millions of “what-if” scenarios to be executed rapidly on thousands of GPUs of Summit and similar supercomputers. An SEIR-based epidemiological model is outlined for numerous what-if simulations of disease spread that can be executed for country-scale populations like India’s, with ‘what-if’ scenarios, each varying in the outbreak points (hotspots), quarantines, vaccinations and hospitalizations.
A machine learning pipeline for the prediction of material structure properties directly from their neutron scattering profiles (development as part of the ExaLearn ECP co-design project). A brief overview of this system is provided, which is being applied for studies of new therapeutic targets and viral protein-structure-assisted drug design studies related to the COVID outbreak.
Network science methods are outlined for detecting information cascades in time varying large-scale social communication networks. We discuss its implications for detecting occurrence/response or epidemic related events from Twitter and similar global interaction systems.

Energy Conservation Through Cloned Execution Of Simulations

Sun, 08 Dec 2019 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/9004821

Exact-Differential Simulation: Differential Processing of Large-Scale Discrete Event Simulations

Tue, 18 Jun 2019 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3301499

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Wed, 31 Jan 2018 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3158669

Efficient Simulation of Nested Hollow Sphere Intersections: for Dynamically Nested Compartmental Models in Cell Biology

Tue, 16 May 2017 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3064911.3064920

Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

Wed, 10 Feb 2016 00:00:00 +0000

Andelfinger’s thesis online

Efficient Parallel Discrete Event Simulation on Cloud/Virtual Machine Platforms

Thu, 01 Jan 2015 00:00:00 +0000

[Pub 149]

http://tomacs.acm.org/

Virtual Time-Aware Virtual Machine Systems

Tue, 01 Jul 2014 00:00:00 +0000

https://smartech.gatech.edu/bitstream/handle/1853/52321/YOGINATH-DISSERTATION-2014.pdf

Design of A High-Fidelity Testing Framework for Secure Electric Grid Control

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 144]

http://wintersim.org

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 121]

http://tomacs.acm.org

Parallel Discrete Event Simulation

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 147]

http://hpcs2014.cisedu.info/

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 119]

http://link.springer.com/article/10.1007%2Fs10586-013-0277-4

Simulating Billion-Task Parallel Programs

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 143]

http://atc.udg.edu/SPECTS2014/

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 148]

http://www.scs.org/jdms

Simulation des Réseaux à grande Échelle sur les architectures de calcules hètèrogénes

Sun, 01 Dec 2013 00:00:00 +0000

Romdhanne’s thesis online

Empirical Evaluation of PDES Execution on Cloud and Virtual Machine Platforms

Tue, 01 Jan 2013 00:00:00 +0000

[Pub 135]

http://www.acm-sigsim-pads.org/

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

Tue, 01 Jan 2013 00:00:00 +0000

[Pub 134]

http://simutools.org/2013

Discrete Event Execution and Reversibility: Challenges in the Path to Asynchrony for Massively Parallel Computing

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 127]

http://www.siam.org/meetings/jmm12/

Parallel Simulation on Supercomputers

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 125]

http://www.wintersim.org

Runtime Performance And Virtual Network Control Alternatives In VM-Based High-Fidelity Network Simulations

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 126]

http://www.wintersim.org

Taming Wild Horses: The Need for Virtual Time-based Scheduling of VMs in Network Simulations

Sun, 01 Jan 2012 00:00:00 +0000

[Pub 133]

http://mascots.cs.vt.edu

Efficiently Scheduling Multi-core Guest Virtual Machines on Multi-core Hosts in Network Simulation

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 129]

http://sites.google.com/site/pads2011/

GVT Algorithms and Discrete Event Dynamics on 129K+ Processor Cores

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 132]

http://www.hipc.org/hipc2011

Improving Multi-Million Virtual Rank MPI Execution in MUPI

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 131]

http://pdcc.ntu.edu.sg/mascots2011/

Towards High Performance Discrete Event Simulations of Smart Electric Grids

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 130]

Discrete-Event Execution Alternatives on GPGPUs

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 33]

Integrated Analysis of Environment-Driven Operational Effects in Sensor Networks

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 70]

Network Simulation

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 3]

http://www.morganclaypool.com/toc/cnt/1/1

On Evaluation Needs of Real-life Sensor Network Deployments

Sun, 01 Jan 2006 00:00:00 +0000

[Pub 18]

A Federated Approach to Distributed Network Simulation

Thu, 01 Jan 2004 00:00:00 +0000

[Pub 12]

Conservative Synchronization of Large-scale Network Simulations

Thu, 01 Jan 2004 00:00:00 +0000

[Pub 43]

Large-Scale Network Simulation - How Big? How Fast?

Wed, 01 Jan 2003 00:00:00 +0000

[Pub 44]

Scalable RTI-based Parallel Simulation of Networks

Wed, 01 Jan 2003 00:00:00 +0000

[Pub 46]

The High Level Architecture for Simulation

Fri, 01 Jan 1999 00:00:00 +0000

[Pub 87]

A C++ Instance of TeD

Mon, 01 Jan 1996 00:00:00 +0000

[Pub 78]

Discrete | Kalyan Perumalla

DarkNet Cyber Resilience

Overview

Key Links

Gallery

Organization

Selected Publications

NAERM

Overview

Contributions

Architecture

Demo Videos

Description

Organization

ZeroIn

Overview

Related Publications

Organization

Gallery

DES Grid

Overview

Gallery

Approach

Organization

Additional Motivation

Selected Publications

Digital Twin Framework

Overview

Organization

Gallery

Related Publications

EpiClone: Epidemiological Clonable Simulations

Overview

Gallery

Organization

Related Publications

Network Simulation

Overview

Reference

CloneX

Overview

Organization

Gallery

Related Publications

HELICS

Overview

Organization

NetWarp

Organization

Gallery

Related Publications

Rocks3D-HPC

Organization

Gallery

RealSim: Real-Time Simulations

Gallery

Organization

Related Publications

Exploratory Research for Extreme-Scale Science (EXPRESS)

Awards

Solicitation PDF

Selected Pages

Selected Extracts

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs: Fast What–If Analyses of Localized and Dynamic Effects

A Case Study in Simulation Methods for Power Electronic Circuits

COVID-relevant Scalable Computational Research Directions and Tools

Energy Conservation Through Cloned Execution Of Simulations

Exact-Differential Simulation: Differential Processing of Large-Scale Discrete Event Simulations

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Efficient Simulation of Nested Hollow Sphere Intersections: for Dynamically Nested Compartmental Models in Cell Biology

Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

Efficient Parallel Discrete Event Simulation on Cloud/Virtual Machine Platforms

Virtual Time-Aware Virtual Machine Systems

Design of A High-Fidelity Testing Framework for Secure Electric Grid Control

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Parallel Discrete Event Simulation

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Simulating Billion-Task Parallel Programs

Virtual Machine-Based Simulation Platform For MANET-Based Cyber Infrastructure