scholarly journals A population data-driven workflow for COVID-19 modeling and learning

2021 ◽  
Vol 35 (5) ◽  
pp. 483-499
Author(s):  
Jonathan Ozik ◽  
Justin M Wozniak ◽  
Nicholson Collier ◽  
Charles M Macal ◽  
Mickaël Binois
Keyword(s):  
Social Interactions ◽  
High Performance ◽  
Large Scale ◽  
Population Data ◽  
Crisis Response ◽  
Protective Behaviors ◽  
Activity Schedules ◽  
Heterogeneous Agent ◽  
Agent Based ◽  
Disease States

CityCOVID is a detailed agent-based model that represents the behaviors and social interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 million distinct places, including households, schools, workplaces, and hospitals, as determined by individual hourly activity schedules and dynamic behaviors such as isolating because of symptom onset. Disease progression dynamics incorporated within each agent track transitions between possible COVID-19 disease states, based on heterogeneous agent attributes, exposure through colocation, and effects of protective behaviors of individuals on viral transmissibility. Throughout the COVID-19 epidemic, CityCOVID model outputs have been provided to city, county, and state stakeholders in response to evolving decision-making priorities, while incorporating emerging information on SARS-CoV-2 epidemiology. Here we demonstrate our efforts in integrating our high-performance epidemiological simulation model with large-scale machine learning to develop a generalizable, flexible, and performant analytical platform for planning and crisis response.

scholarly journals Real-time Analysis of City Scale Transportation Networks in New Orleans Metropolitan Area using an Agent Based Model Approach

2019 ◽  
Vol 271 ◽  
pp. 06007
Author(s):  
Millard McElwee ◽  
Bingyu Zhao ◽  
Kenichi Soga
Keyword(s):  
New Orleans ◽  
Real Time ◽  
High Performance ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Regional Scale ◽  
Agent Based Model ◽  
Agent Based ◽  
Real Time Analysis

The primary focus of this research is to develop and implement an agent-based model (ABM) to analyze the New Orleans Metropolitan transportation network near real-time. ABMs have grown in popularity because of their ability to analyze multifaceted community scale resilience with hundreds of thousands of links and millions of agents. Road closures and reduction in capacities are examples of influences on the weights or removal of edges which can affect the travel time, speed, and route of agents in the transportation model. Recent advances in high-performance computing (HPC) have made modeling networks on the city scale much less computationally intensive. We introduce an open-source ABM which utilizes parallel distributed computing to enable faster convergence to large scale problems. We simulate 50,000 agents on the entire southeastern Louisiana road network and part of Mississippi as well. This demonstrates the capability to simulate both city and regional scale transportation networks near real time.

Large-Scale Social Simulation, Dealing with Complexity Challenges in High Performance Environments

2014 ◽  
pp. 106-123 ◽  
Author(s):  
C. Montañola-Sales ◽  
X. Rubio-Campillo ◽  
J. Casanovas-Garcia ◽  
J. M. Cela-Espín ◽  
A. Kaplan-Marcusán
Keyword(s):  
Information Technology ◽  
Computer Simulations ◽  
Real World ◽  
High Performance ◽  
Large Scale ◽  
Social Dynamics ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Important Amount ◽  
Distributed Implementation

Advances on information technology in the past decades have provided new tools to assist scientists in the study of social and natural phenomena. Agent-based modeling techniques have flourished recently, encouraging the introduction of computer simulations to examine behavioral patterns in complex human and biological systems. Real-world social dynamics are very complex, containing billions of interacting individuals and an important amount of data (both spatial and social). Dealing with large-scale agent-based models is not an easy task and encounters several challenges. The design of strategies to overcome these challenges represents an opportunity for high performance parallel and distributed implementation. This chapter examines the most relevant aspects to deal with large-scale agent-based simulations in social sciences and revises the developments to confront technological issues.

scholarly journals DAPT: A package enabling distributed automated parameter testing

Gigabyte ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ben Duggan ◽  
John Metzcar ◽  
Paul Macklin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Ad Hoc ◽  
Simulation Models ◽  
Power Combining ◽  
Agent Based ◽  
Tool Set ◽  
Computational Resources ◽  
Performance Computing ◽  
Python Package

Modern agent-based models (ABM) and other simulation models require evaluation and testing of many different parameters. Managing that testing for large scale parameter sweeps (grid searches), as well as storing simulation data, requires multiple, potentially customizable steps that may vary across simulations. Furthermore, parameter testing, processing, and analysis are slowed if simulation and processing jobs cannot be shared across teammates or computational resources. While high-performance computing (HPC) has become increasingly available, models can often be tested faster with the use of multiple computers and HPC resources. To address these issues, we created the Distributed Automated Parameter Testing (DAPT) Python package. By hosting parameters in an online (and often free) “database”, multiple individuals can run parameter sets simultaneously in a distributed fashion, enabling ad hoc crowdsourcing of computational power. Combining this with a flexible, scriptable tool set, teams can evaluate models and assess their underlying hypotheses quickly. Here, we describe DAPT and provide an example demonstrating its use.

A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems

2010 ◽  
pp. 566-588 ◽  
Author(s):  
Florin Pop
Keyword(s):  
Distributed Systems ◽  
High Performance ◽  
Large Scale ◽  
Fault Tolerant ◽  
Optimal Algorithm ◽  
Distributed Applications ◽  
Distributed Scheduling ◽  
Agent Based ◽  
Decentralized Scheduling ◽  
Optimization Schemes

This chapter presents a fault tolerant framework for the applications scheduling in large scale distributed systems (LSDS). Due to the specific characteristics and requirements of distributed systems, a good scheduling model should be dynamic. More specifically, it should adapt the scheduling decisions to resource state changes, which are commonly captured through monitoring. The scheduler and the monitor are two important middleware pieces that correlate their actions to ensure the high performance execution of distributed applications. The chapter presents and analyses agent based architecture for scheduling in large scale distributed systems. Then the user and resources management are presented. Optimization schemes for scheduling consider the near-optimal algorithm for distributed scheduling. The chapter presents the solution for scheduling optimization. The chapter covers and explains the fault tolerance cases for Grid environments and describes two possible scenarios for scheduling system.

AN AGENT-BASED MODEL OF HUMAN DISPERSALS AT A GLOBAL SCALE

2013 ◽  
Vol 16 (04n05) ◽  
pp. 1350023 ◽  
Author(s):  
SIMONE CALLEGARI ◽  
JOHN DAVID WEISSMANN ◽  
NATALIE TKACHENKO ◽  
WESLEY P. PETERSEN ◽  
GEORGE LAKE ◽  
...  
Keyword(s):  
Population Dynamics ◽  
High Performance ◽  
Large Scale ◽  
Global Scale ◽  
Small Scale ◽  
Emergent Properties ◽  
Agent Based ◽  
Human Dispersal ◽  
Model Hierarchy ◽  
Empirical Context

In this paper, we report on the theoretical foundations, empirical context and technical implementation of an agent-based modeling (ABM) framework, that uses a high-performance computing (HPC) approach to investigate human population dynamics on a global scale, and on evolutionary time scales. The ABM-HPC framework provides an in silico testbed to explore how short-term/small-scale patterns of individual human behavior and long-term/large-scale patterns of environmental change act together to influence human dispersal, survival and extinction scenarios. These topics are currently at the center of the Neanderthal debate, i.e., the question why Neanderthals died out during the Late Pleistocene, while modern humans dispersed over the entire globe. To tackle this and similar questions, simulations typically adopt one of two opposing approaches, top-down (equation-based) and bottom-up (agent-based) models of population dynamics. We propose HPC technology as an essential computational tool to bridge the gap between these approaches. Using the numerical simulation of worldwide human dispersals as an example, we show that integrating different levels of model hierarchy into an ABM-HPC simulation framework provides new insights into emergent properties of the model, and into the potential and limitations of agent-based versus continuum models.

scholarly journals DAPT: A Package Enabling Distributed Automated Parameter Testing

2021 ◽  
Author(s):  
Ben Duggan ◽  
John Metzcar ◽  
Paul Macklin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Ad Hoc ◽  
Simulation Models ◽  
Power Combining ◽  
Agent Based ◽  
Tool Set ◽  
Computational Resources ◽  
Performance Computing ◽  
Python Package

Modern agent-based models (ABM) and other simulation models require evaluation and testing of many different parameters. Managing that testing for large scale parameter sweeps (grid searches) as well as storing simulation data requires multiple, potentially customizable steps that may vary across simulations. Furthermore, parameter testing, processing, and analysis are slowed if simulation and processing jobs cannot be shared across teammates or computational resources. While high-performance computing (HPC) has become increasingly available, models can often be tested faster through the use of multiple computers and HPC resources. To address these issues, we created the Distributed Automated Parameter Testing (DAPT) Python package. By hosting parameters in an online (and often free) "database", multiple individuals can run tests simultaneously in a distributed fashion, enabling ad hoc crowdsourcing of computational power. Combining this with a flexible, scriptable tool set, teams can evaluate models and assess their underlying hypotheses quickly. Here we describe DAPT and provide an example demonstrating its use.

scholarly journals DAPT: A Package Enabling Distributed Automated Parameter Testing

2021 ◽  
Author(s):  
Ben Duggan ◽  
John Metzcar ◽  
Paul Macklin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Ad Hoc ◽  
Simulation Models ◽  
Power Combining ◽  
Agent Based ◽  
Tool Set ◽  
Computational Resources ◽  
Performance Computing ◽  
Python Package

Modern agent-based models (ABM) and other simulation models require evaluation and testing of many different parameters. Managing that testing for large scale parameter sweeps (grid searches) as well as storing simulation data requires multiple, potentially customizable steps that may vary across simulations. Furthermore, parameter testing, processing, and analysis are slowed if simulation and processing jobs cannot be shared across teammates or computational resources. While high-performance computing (HPC) has become increasingly available, models can often be tested faster through the use of multiple computers and HPC resources. To address these issues, we created the Distributed Automated Parameter Testing (DAPT) Python package. By hosting parameters in an online (and often free) "database", multiple individuals can run parameter sets simultaneously in a distributed fashion, enabling ad hoc crowdsourcing of computational power. Combining this with a flexible, scriptable tool set, teams can evaluate models and assess their underlying hypotheses quickly. Here we describe DAPT and provide an example demonstrating its use.

scholarly journals Social identity and meat consumption - An agent-based model

2021 ◽  
Author(s):  
Jiaqi Ge ◽  
Andrea Scalco ◽  
Tony Craig
Keyword(s):  
Social Identity ◽  
Social Interactions ◽  
Large Scale ◽  
Eating Behaviour ◽  
System Level ◽  
Dietary Behaviour ◽  
Agent Based Model ◽  
Agent Based ◽  
Meat Eating ◽  
Group Members

Humans are social animals. Even the very personal decision of what someone eats is influenced by others around them. In this study, we propose four social interaction mechanisms driven by social identity that affect a person’s decision to eat or not eat meat. Using data from the British Social Attitude Survey in 2014, we operationalise social identity in an agent-based model to study the effect of social interactions on the spread of meat-eating behaviour in the British population. We find that social interactions are crucial in determining the spread of meat-eating behaviour. In order to bring about large-scale behavioural changes at the system level, people need to 1) have a strong openness to influences from both in-group and out-group members who have a different dietary behaviour, and 2) have a weak tendency to reinforce their current behaviour after seeing in-group members sharing the same behaviour. The agent-based model is shown to be a useful tool to operationalise social theories in a well-defined context, and to upscale the system to study its dynamic evolutions under different scenarios.

The Structure and Properties of MoSi2 Thin Film in Mos Process

1980 ◽  
Vol 38 ◽  
pp. 326-327
Author(s):  
C.K. Wu ◽  
P. Chang ◽  
N. Godinho
Keyword(s):  
Thin Film ◽  
Integrated Circuits ◽  
High Performance ◽  
Large Scale ◽  
Process Development ◽  
Structure And Properties ◽  
Metal Silicides ◽  
High Oxidation ◽  
Important Approach ◽  
High Oxidation Resistance

Recently, the use of refractory metal silicides as low resistivity, high temperature and high oxidation resistance gate materials in large scale integrated circuits (LSI) has become an important approach in advanced MOS process development (1). This research is a systematic study on the structure and properties of molybdenum silicide thin film and its applicability to high performance LSI fabrication.

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