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gpu-Accelerated Minimum Distance and Clearance Queries

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2011年第6期17卷 729-742页

作者： Krishnamurthy, Adarsh McMains, Sara Haller, Kirk Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA Dassault Syst SolidWorks Corp Concord MA 01742 USA

We present practical algorithms for accelerating distance queries on models made of trimmed NURBS surfaces using programmable Graphics Processing Units (gpus). We provide a generalized framework for using gpus as coprocessors in accelerating CAD operations. By supplementing surface data with a surface bounding-box hierarchy on the gpu, we answer distance queries such as finding the closest point on a curved NURBS surface given any point in space and evaluating the clearance between two solid models constructed using multiple NURBS surfaces. We simultaneously output the parameter values corresponding to the solution of these queries along with the model space values. Though our algorithms make use of the programmable fragment processor, the accuracy is based on the model space precision, unlike earlier graphics algorithms that were based only on image space precision. In addition, we provide theoretical bounds for both the computed minimum distance values as well as the location of the closest point. Our algorithms are at least an order of magnitude faster and about two orders of magnitude more accurate than the commercial solid modeling kernel ACIS.

关键词： Minimum distance closest point clearance analysis NURBS gpu hybrid cpu/gpu algorithms

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Accurate gpu-accelerated surface integrals for moment computation

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COMPUTER-AIDED DESIGN 2011年第10期43卷 1284-1295页

作者： Krishnamurthy, Adarsh McMains, Sara Univ Calif Berkeley Comp Aided Design & Mfg Lab Berkeley CA 94720 USA

We present algorithms for computing accurate moments of solid models that are represented using multiple trimmed NURBS surfaces and triangles. Our algorithms make use of programmable Graphics Processing Units (gpus) to accelerate the moment computations. For NURBS surfaces, we evaluate the surface coordinates and normals accurately, with theoretical bounds, using our cpu NURBS evaluator. We have developed a framework that makes use of this data to evaluate surface integrals of trimmed NURBS surfaces in real time. Since typical solid models also contain flat planes that are usually tessellated into triangles, our framework also includes cpu acceleration of the moment contributions of such flat faces. Using our framework, we can compute volume and moments of solid models with theoretical guarantees. Our algorithms support local geometry changes, which is useful for providing interactive feedback to the designer while the solid model is being designed. We can compute the center of mass and check for stability of the solid model interactively. Other applications of such real-time moment computation include deformation modeling, animation, and physically based simulations. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Geometric algorithms Moments Volume NURBS gpu hybrid cpu/gpu algorithms

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Accurate gpu-accelerated surface integrals for moment computation

Accurate GPU-accelerated surface integrals for moment comput...

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ACM 15th Symposium on Solid and Physical Modeling (SPM)

作者： Krishnamurthy, Adarsh McMains, Sara Univ Calif Berkeley Comp Aided Design & Mfg Lab Berkeley CA 94720 USA

关键词： Geometric algorithms Moments Volume NURBS gpu hybrid cpu/gpu algorithms

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