Racing to hardware-validated simulation

Processor simulators rely on detailed timing models of the processor pipeline to evaluate performance. The diversity in real-world processor designs mandates building flexible simulators that expose parts of the underlying model to the user in the form of configurable parameters. Consequently, the accuracy of modeling a real processor relies on both the accuracy of the pipeline model itself, and the accuracy of adjusting the configuration parameters according to the modeled processor. Unfortunately, processor vendors publicly disclose only a subset of their design decisions, raising the probability of introducing specification inaccuracies when modeling these processors. Inaccurately tuning model parameters deviates the simulated processor from the actual one. In the worst case, using improper parameters may lead to imbalanced pipeline models compromising the simulation output. Therefore, simulation models should be hardware-validated before using them for performance evaluation. As processors increase in complexity and diversity, validating a simulator model against real hardware becomes increasingly more challenging and time-consuming. In this work, we propose a methodology for validating simulation models against real hardware. We create a framework that relies on micro-benchmarks to collect performance statistics on real hardware, and machine learning-based algorithms to fine-tune the unknown parameters based on the accumulated statistics. We overhaul the Sniper simulator to support the ARM AArch64 instruction-set architecture (ISA), and introduce two new timing models for ARM-based in-order and out-of-order cores. Using our proposed simulator validation framework, we tune the in-order and out-of-order models to match the performance of a real-world implementation of the Cortex-A53 and Cortex-A72 cores with an average error of 7% and 15%, respectively, across a set of SPEC CPU2017 benchmarks

Impact of climate change using CRAFT: a case study for West Africa

The CGIAR research program on Climate Change, Agriculture and Food Security Program’s (CCAFS) Regional Agricultural Forecasting Toolbox (CRAFT) is a framework for multi-scale spatial gridded simulations using an ensemble of crop models. The toolbox facilitates studies on the potential impact of climate change on crop production for a region in addition to other capabilities such as the regional in-season yield forecasting and risk assessment. CRAFT can be used to generate and conduct multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the crop simulation models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for probabilistic seasonal climate forecasts

Eine präzise Multilevel-Testbench zur Systemsimulation und Charakterisierung einer 2,5 GHz PLL

In diesem Aufsatz wird eine präzise Multilevel-Testbench zur PLL-Charakterisierung vorgestellt. Die Schwerpunkte dieses Beitrags sind einerseits das 10 GHz VCO-Design und andererseits die vorhersagefähigen Ergebnisse der mit Hilfe dieses Multilevelansatzes durchgeführten PLL-Systemsimulationen. <br><br> Bei dem VCO-Design wurden folgende Ergebnisse erreicht: Abstimmbereich ≈26% bzw. kvco≈1300 MHz/V, Phasenrauschen PN=–101,4 dBc/Hz @1 MHz Offset vom 10 GHz Träger, Leistungsverbrauch = 5,5 mW. Als realistisches Demonstrationsbeispiel ist das „analog mixed signal“-Verhalten eines 2,5 GHz PLL-Systems für „dual-conversion“-Strukturen bei IEEE 802.11a WLAN-Anwendungen gewählt worden. Für dieses Beispiel wird eine effiziente PLL-Modellierung kritischer PLL-Blöcke (Frequenzteiler und Phasenfrequenzdetektor) auf der Basis der PSS-Analyse und neuer Verilog-A/MS Befehle demonstriert. Die dabei verwendete Testbench kann im Prinzip in verschiedenen aktuellen Wireless Kommunikationssystemen bis 10 GHz wieder verwendet werden (Reuse-IP). Dieser Ansatz führt einerseits zur Verbesserung der Simulationszeiten (verglichen mit dem Transistorlevel) und andererseits zu genaueren und realistischeren Ergebnissen, vor allem am VCO-Ausgang (verglichen mit dem HDL-Level)

Liquid-gas-solid flows with lattice Boltzmann: Simulation of floating bodies

This paper presents a model for the simulation of liquid-gas-solid flows by means of the lattice Boltzmann method. The approach is built upon previous works for the simulation of liquid-solid particle suspensions on the one hand, and on a liquid-gas free surface model on the other. We show how the two approaches can be unified by a novel set of dynamic cell conversion rules. For evaluation, we concentrate on the rotational stability of non-spherical rigid bodies floating on a plane water surface - a classical hydrostatic problem known from naval architecture. We show the consistency of our method in this kind of flows and obtain convergence towards the ideal solution for the measured heeling stability of a floating box.Comment: 22 pages, Preprint submitted to Computers and Mathematics with Applications Special Issue ICMMES 2011, Proceedings of the Eighth International Conference for Mesoscopic Methods in Engineering and Scienc

CAD Model-based 3D Object Pose Estimation using an Edge-Based Nonlinear Model Fitting Algorithm

[[abstract]]This paper addresses the design of a model-based 3D object pose estimation algorithm, which is one of the major techniques to develop a robust robotic vision system using a monocular camera. The proposed system first extracts line features of a captured image by using edge detection and Hough transform techniques. Given a CAD model of the object-of-interest, the 6-DOF pose of the object can then be estimated via a novel edge-based nonlinear model fitting algorithm, which is a nonlinear optimization process for estimating the optimal object pose based on an edge-based distance metric. Experimental results validate the performance of the proposed system.[[notice]]補正完

Permeability of porous materials determined from the Euler characteristic

We study the permeability of quasi two-dimensional porous structures of randomly placed overlapping monodisperse circular and elliptical grains. Measurements in microfluidic devices and lattice Boltzmann simulations demonstrate that the permeability is determined by the Euler characteristic of the conducting phase. We obtain an expression for the permeability that is independent of the percolation threshold and shows agreement with experimental and simulated data over a wide range of porosities. Our approach suggests that the permeability explicitly depends on the overlapping probability of grains rather than their shape

Use of Indicators to Evaluate Sustainability of Animal Production Systems

SUMMARY – Few indicators for sustainability are used in studying animal production systems. Sustainability of these systems should be evaluated in a dynamic and multidisciplinary manner, and those indicators used should allow for detecting the systems' most relevant properties, as well as the tendency of those systems to change. Indicators proposed by FAO provide information regarding all attributes of sustainability, although in a manner which is overly focused on technical and economic indicators at the expense of social and environmental factors. In order to use these indicators to evaluate sustainability, it is necessary to: (i) integrate and reduce the number of indicators, balancing them for all sustainability attributes; (ii) generate indicators which show system sustainability in relation to the economic, environmental and social context; and (iii) design indicators which show system evolution and the influence of this process on that system’s sustainability.RESUME – "Utilisation d'indicateurs pour évaluer la durabilité des systèmes de production animale". Les indicateurs permettant de caractériser la durabilité des systèmes de production animale sont peu développés. L'évaluation de la durabilité de ces systèmes doit être dynamique et multidisciplinaire et les indicateurs utilisés doivent permettre de détecter les caractéristiques les plus importantes des systèmes et leur évolution. Les indicateurs proposés par la FAO servent à informer sur tous les attributs liés à la durabilité, mais d’une façon non équilibrée et trop centrée sur le système de production. Pour rendre possible l’utilisation des indicateurs FAO en tant qu'évaluateurs de la durabilité des systèmes, il conviendra de: (i) réduire le nombre d'indicateurs obtenus à partir des données de l’exploitation, en cherchant un équilibre entre le nombre d’indicateurs qui correspondent à chaque attribut de la durabilité ; (ii) générer des indicateurs représentatifs de la durabilité des systèmes liés à l'environnement, aussi bien physique, économique que social ; et (iii) créer des indicateurs qui renseignent sur l’évolution du système et de sa durabilité

Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs

The great learning ability of deep learning models facilitates us to comprehend the real physical world, making learning to simulate complicated particle systems a promising endeavour. However, the complex laws of the physical world pose significant challenges to the learning based simulations, such as the varying spatial dependencies between interacting particles and varying temporal dependencies between particle system states in different time stamps, which dominate particles' interacting behaviour and the physical systems' evolution patterns. Existing learning based simulation methods fail to fully account for the complexities, making them unable to yield satisfactory simulations. To better comprehend the complex physical laws, this paper proposes a novel learning based simulation model- Graph Networks with Spatial-Temporal neural Ordinary Equations (GNSTODE)- that characterizes the varying spatial and temporal dependencies in particle systems using a united end-to-end framework. Through training with real-world particle-particle interaction observations, GNSTODE is able to simulate any possible particle systems with high precisions. We empirically evaluate GNSTODE's simulation performance on two real-world particle systems, Gravity and Coulomb, with varying levels of spatial and temporal dependencies. The results show that the proposed GNSTODE yields significantly better simulations than state-of-the-art learning based simulation methods, which proves that GNSTODE can serve as an effective solution to particle simulations in real-world application.Comment: 12 pages,5 figures, 6 tables, 49 reference