Scalable RTI-Based Parallel Simulation of Networks

©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at the Seventeenth Workshop on Parallel and Distributed Simulation (PADS 03), 2003Federated simulation interfaces such as the High Level Architecture (HLA) were designed for interoperability, and as such are not traditionally associated with high performance computing. In this paper, we present results of a case study examining the use of federated simulations using runtime infrastructure (RTI) software to realize large-scale parallel network simulators. We examine the performance of two different federated network simulators, and describe RTI performance optimizations that were used to achieve efficient execution. We show that RTI-based parallel simulations can scale extremely well and achieve very high speedup. Our experiments yielded more than 80-fold scaled speedup in simulating large TCP/IP networks, demonstrating performance of up to 6 million simulated packet transmissions per second on a Linux cluster. Networks containing up to two million network nodes (routers and end systems) were simulated

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of 13 electronic ground-state properties of organic molecules. The performance of each regressor/representation/property combination is assessed using learning curves which report out-of-sample errors as a function of training set size with up to ∼118k distinct molecules. Molecular structures and properties at the hybrid density functional theory (DFT) level of theory come from the QM9 database [Ramakrishnan et al. Sci. Data 2014, 1, 140022] and include enthalpies and free energies of atomization, HOMO/LUMO energies and gap, dipole moment, polarizability, zero point vibrational energy, heat capacity, and the highest fundamental vibrational frequency. Various molecular representations have been studied (Coulomb matrix, bag of bonds, BAML and ECFP4, molecular graphs (MG)), as well as newly developed distribution based variants including histograms of distances (HD), angles (HDA/MARAD), and dihedrals (HDAD). Regressors include linear models (Bayesian ridge regression (BR) and linear regression with elastic net regularization (EN)), random forest (RF), kernel ridge regression (KRR), and two types of neural networks, graph convolutions (GC) and gated graph networks (GG). Out-of sample errors are strongly dependent on the choice of representation and regressor and molecular property. Electronic properties are typically best accounted for by MG and GC, while energetic properties are better described by HDAD and KRR. The specific combinations with the lowest out-of-sample errors in the ∼118k training set size limit are (free) energies and enthalpies of atomization (HDAD/KRR), HOMO/LUMO eigenvalue and gap (MG/GC), dipole moment (MG/GC), static polarizability (MG/GG), zero point vibrational energy (HDAD/KRR), heat capacity at room temperature (HDAD/KRR), and highest fundamental vibrational frequency (BAML/RF). We present numerical evidence that ML model predictions deviate from DFT (B3LYP) less than DFT (B3LYP) deviates from experiment for all properties. Furthermore, out-of-sample prediction errors with respect to hybrid DFT reference are on par with, or close to, chemical accuracy. The results suggest that ML models could be more accurate than hybrid DFT if explicitly electron correlated quantum (or experimental) data were available

Bootstrapping in Gnutella: A Preliminary Measurement Study

To join an unstructured peer-to-peer network like Gnutella, peers have to execute a bootstrapping function in which they discover other on-line peers and connect to them. Until this bootstrapping step is complete, a peer cannot participate in file sharing activities. Once bootstrapping is complete, a peer’s experience is strongly influenced by the choice of neighbor peers resulting from the bootstrapping step. Despite its importance, there has been very little attention devoted to understanding the behavior of this bootstrapping function. In this paper, we study the bootstrapping process of a peer in the Gnutella network. This is a preliminary investigation, consisting of 1) an analysis and performance comparison of bootstrapping algorithms of four Gnutella servent implementations, 2) a measurement-based characterization of the global Gnutella Web Caching System (GWebCaches), a primary component of the current bootstrapping functions, and 3) a study of the behavior and experience of a single GWebCache that was setup locally and made part of the global caching infrastructure. Our study highlights the importance of understanding the performance of the bootstrapping function as an integral part of a peer-to-peer system. We find that 1) there is considerable variation among various servent implementations that correlates to their bootstrapping performance, 2) even though the GWebCache system is designed to operate as a truly distributed system in keeping with the peer-to-peer system philosophy, it actually operates more like a centralized infrastructure function, and 3) the GWebCache system is subject to misreporting of peer and cache availability due to stale data and absence of validity checks

Limits on Neutrino Oscillations from the CHOOZ Experiment

We present new results based on the entire CHOOZ data sample. We find (at 90% confidence level) no evidence for neutrino oscillations in the anti_nue disappearance mode, for the parameter region given by approximately Delta m**2 > 7 x 10**-4 eV^2 for maximum mixing, and sin**2(2 theta) = 0.10 for large Delta m**2. Lower sensitivity results, based only on the comparison of the positron spectra from the two different-distance nuclear reactors, are also presented; these are independent of the absolute normalization of the anti_nue flux, the cross section, the number of target protons and the detector efficiencies.Comment: 19 pages, 11 figures, Latex fil

Search for neutrino oscillations on a long base-line at the CHOOZ nuclear power station

This final article about the CHOOZ experiment presents a complete description of the electron antineutrino source and detector, the calibration methods and stability checks, the event reconstruction procedures and the Monte Carlo simulation. The data analysis, systematic effects and the methods used to reach our conclusions are fully discussed. Some new remarks are presented on the deduction of the confidence limits and on the correct treatment of systematic errors.Comment: 41 pages, 59 figures, Latex file, accepted for publication by Eur.Phys.J.

Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach

This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.J.M. Angulo and A.E. Madrid have been partially supported by grants MTM2009-13250 and MTM2012-32666 of SGPI, and P08-FQM-3834 of the Andalusian CICE, Spain. H-L Yu has been partially supported by a grant from National Science Council of Taiwan (NSC101-2628-E-002-017-MY3 and NSC102-2221-E-002-140-MY3). A. Kolovos was supported by SpaceTimeWorks, LLC. G. Christakos was supported by a Yongqian Chair Professorship (Zhejiang University, China)

Defining the phylogenetics and resistome of the major clostridioides difficile ribotypes circulating in Australia

Clostridioides difficile infection (CDI) remains a significant public health threat globally. New interventions to treat CDI rely on an understanding of the evolution and epidemiology of circulating strains. Here we provide longitudinal genomic data on strain diversity, transmission dynamics and antimicrobial resistance (AMR) of C. difficile ribotypes (RTs) 014/020 (n=169), 002 (n=77) and 056 (n=36), the three most prominent C. difficile strains causing CDI in Australia. Genome scrutiny showed that AMR was uncommon in these lineages, with resistance-conferring alleles present in only 15/169 RT014/020 strains (8.9 %), 1/36 RT056 strains (2.78 %) and none of 77 RT002 strains. Notably, ~90 % of strains were resistant to MLSB agents in vitro, but only ~5.9 % harboured known resistance alleles, highlighting an incongruence between AMR genotype and phenotype. Core genome analyses revealed all three RTs contained genetically heterogeneous strain populations with limited evidence of clonal transmission between CDI cases. The average number of pairwise core genome SNP (cgSNP) differences within each RT group ranged from 23.3 (RT056, ST34, n=36) to 115.6 (RT002, ST8, n=77) and 315.9 (RT014/020, STs 2, 13, 14, 49, n=169). Just 19 clonal groups (encompassing 40 isolates), defined as isolates differing by ≤2 cgSNPs, were identified across all three RTs (RT014/020, n=14; RT002, n=3; RT056, n=2). Of these clonal groups, 63 % (12/19) comprised isolates from the same Australian State and 37 % (7/19) comprised isolates from different States. The low number of plausible transmission events found for these major RTs (and previously documented populations in animal and environmental sources/reservoirs) points to widespread and persistent community sources of diverse C. difficile strains as opposed to ongoing nationwide healthcare outbreaks dominated by a single clone. Together, these data provide new insights into the evolution of major lineages causing CDI in Australia and highlight the urgent need for enhanced surveillance, and for public health interventions to move beyond the healthcare setting and into a One Health paradigm to effectively combat this complex pathogen

Fear of crime on the rail networks: Perceptions of the UK public and British Transport Police

Counter-terrorism on the rail network is vital to the security of the United Kingdom. The British Transport Police (BTP) employ covert and overt security measures to prevent crime, which includes: closed circuit television, armed police, unarmed polisce, police community support officers, police dogs, stops and searches and awareness campaigns. All security measures aim to deter crime while importantly reassuring the public. We surveyed both members of the public and BTP officers about the perceived effectiveness of current security measures, specifically with regards to fear of terrorism. Feelings of reassurance and the perceived effectiveness of security measures were positively related. The most effective and reassuring security measure was the use of armed police; whereas the least effective and reassuring was the use of awareness campaigns. However, interestingly, qualitative analyses suggested that an increase in armed police without informed awareness campaigns would have a negative impact on public reassurance by increasing fear