Power aware early design stage hardware software co-optimization

Co-optimizing hardware and software can lead to substantial performance and energy benefits, and is becoming an increasingly important design paradigm. In scientific computing, power constraints increasingly necessitate the return to specialized chips such as Intel’s MIC or IBM’s Blue-Gene architectures. To enable hardware/software co-design in early stages of the design cycle, we propose a simulation infrastructure methodology by combining high-abstraction performance simulation using Sniper with power modeling using McPAT and custom DRAM power models. Sniper/McPAT is fast — simulation speed is around 2 MIPS on an 8-core host machine — because it uses analytical modeling to abstract away core performance during multi-core simulation. We demonstrate Sniper/McPAT’s accuracy through validation against real hardware; we report average performance and power prediction errors of 22.1% and 8.3%, respectively, for a set of SPEComp benchmarks

Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged NavierStokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation

Microwave Antennas and Circuits Modeling Using Electromagnetic Field Simulator

Electromagnetic field simulators have become a widely used tool in a design process of microwave circuits and systems. A proper usage of electromagnetic (EM) field simulators allows substantial reduction of the design time providing reliable results. In such case the required parameters of the designed circuit can be reached even at the first manufactured prototype in spite of high complexity of the structure. However, EM simulation as a numerical process suffers from systematic and random errors similar to measurement using real equipment. Thus the setting of the EM-field simulator such as a frequency range, mesh properties, usage of PEC and PMC walls etc. has to be done with the highest attention and the simulation results have to be always verified using well-established techniques. The aim of the paper is to demonstrate the selected capability of EM-field simulators with a few examples of antenna and circuit modeling. Also an issue of reliability and simulation errors will be discussed

Parametric modeling for simulation based hypersonic vehicle design

The conceptual design stage offers the most opportunity for innovation and the capability to reveal costly design errors early. Integrating high fidelity design and simulation tools into the conceptual design stage enables engineers to develop design variations quickly and affordably. This work focuses primarily on the development and utilization of parametric modeling methods as they apply to a simulation based design process. It will also address the impacts to conceptual design development time. A blended wing-body (BWB) hypersonic wave rider demonstrates how state-of-the-art solid modeling techniques can be coupled to high fidelity CFD analysis codes to perform top down design. Performance trends are identified for several trade study variations which represent a single iteration through the simulation based design process. Performance metrics are based on interpretations from higher level customer, regulatory, business, and other requirements. The process of cascading these requirements down to the component level is the definition of top-down-design. This bidirectional tracing of requirements allows vehicle development to progress in a manner such that any change of the vehicle can be assessed in terms of the overarching requirements

PREDICTION OF CAVITATION ON SHIPS

The emphasis of this paper is on challenges in simulation of cavitating flows, especially flows around propeller and rudder. First the sources of errors in predictions based on Computational Fluid Dynamics (CFD) are highlighted: the accuracy of geometry, grid quality and fineness, turbulence modeling and cavitation modeling. The interaction between errors from different sources is also discussed. The importance of turbulence in the flow upstream of propeller and the difficulty of accounting for it is described next. Special attention is paid to the prediction of tip-vortex cavitation and to scale effects. Results from simulations are compared to experimental data from SVA Potsdam, except for the full-scale analysis of flow around hull, propeller and rudder, for which no experimental data is available. It is concluded that cavitation can be predicted to a degree which makes simulation an indispensable tool for design and optimization of maritime vessels

Estimating posture-recognition performance in sensing garments using geometric wrinkle modeling

A fundamental challenge limiting information quality obtained from smart sensing garments is the influence of textile movement relative to limbs. We present and validate a comprehensive modeling and simulation framework to predict recognition performance in casual loose-fitting garments. A statistical posture and wrinkle-modeling approach is introduced to simulate sensor orientation errors pertained to local garment wrinkles. A metric was derived to assess fitting, the body-garment mobility. We validated our approach by analyzing simulations of shoulder and elbow rehabilitation postures with respect to experimental data using actual casual garments. Results confirmed congruent performance trends with estimation errors below 4% for all study participants. Our approach allows to estimate the impact of fitting before implementing a garment and performing evaluation studies with it. These simulations revealed critical design parameters for garment prototyping, related to performed body posture, utilized sensing modalities, and garment fitting. We concluded that our modeling approach can substantially expedite design and development of smart garments through early-stage performance analysis