Dimension reduction for Gaussian process emulation: an application to the influence of bathymetry on tsunami heights

High accuracy complex computer models, or simulators, require large resources in time and memory to produce realistic results. Statistical emulators are computationally cheap approximations of such simulators. They can be built to replace simulators for various purposes, such as the propagation of uncertainties from inputs to outputs or the calibration of some internal parameters against observations. However, when the input space is of high dimension, the construction of an emulator can become prohibitively expensive. In this paper, we introduce a joint framework merging emulation with dimension reduction in order to overcome this hurdle. The gradient-based kernel dimension reduction technique is chosen due to its ability to drastically decrease dimensionality with little loss in information. The Gaussian process emulation technique is combined with this dimension reduction approach. Our proposed approach provides an answer to the dimension reduction issue in emulation for a wide range of simulation problems that cannot be tackled using existing methods. The efficiency and accuracy of the proposed framework is demonstrated theoretically, and compared with other methods on an elliptic partial differential equation (PDE) problem. We finally present a realistic application to tsunami modeling. The uncertainties in the bathymetry (seafloor elevation) are modeled as high-dimensional realizations of a spatial process using a geostatistical approach. Our dimension-reduced emulation enables us to compute the impact of these uncertainties on resulting possible tsunami wave heights near-shore and on-shore. We observe a significant increase in the spread of uncertainties in the tsunami heights due to the contribution of the bathymetry uncertainties. These results highlight the need to include the effect of uncertainties in the bathymetry in tsunami early warnings and risk assessments.Comment: 26 pages, 8 figures, 2 table

Mesmerizer: A Effective Tool for a Complete Peer-to-Peer Software Development Life-cycle

In this paper we present what are, in our experience, the best practices in Peer-To-Peer(P2P) application development and how we combined them in a middleware platform called Mesmerizer. We explain how simulation is an integral part of the development process and not just an assessment tool. We then present our component-based event-driven framework for P2P application development, which can be used to execute multiple instances of the same application in a strictly controlled manner over an emulated network layer for simulation/testing, or a single application in a concurrent environment for deployment purpose. We highlight modeling aspects that are of critical importance for designing and testing P2P applications, e.g. the emulation of Network Address Translation and bandwidth dynamics. We show how our simulator scales when emulating low-level bandwidth characteristics of thousands of concurrent peers while preserving a good degree of accuracy compared to a packet-level simulator

An Automated Design-flow for FPGA-based Sequential Simulation

In this paper we describe the automated design flow that will transform and map a given homogeneous or heterogeneous hardware design into an FPGA that performs a cycle accurate simulation. The flow replaces the required manually performed transformation and can be embedded in existing standard synthesis flows. Compared to the earlier manually translated designs, this automated flow resulted in a reduced number of FPGA hardware resources and higher simulation frequencies. The implementation of the complete design flow is work in progress.\u

Network emulation focusing on QoS-Oriented satellite communication

This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication