NDLI: Accelerating geometric queries using the GPU

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Accelerating geometric queries using the GPU

Content Provider	ACM Digital Library
Author	McMains, Sara Krishnamurthy, Adarsh Halle, Kirk
Abstract	We present practical algorithms for accelerating geometric queries on models made of NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as co-processors in accelerating CAD operations. By attaching the data corresponding to surface-normals to a surface bounding-box structure, we can calculate view-dependent geometric features such as silhouette curves in real time. We make use of additional surface data linked to surface bounding-box hierarchies on the GPU to answer 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 than the commercial solid modeling kernel ACIS.
Starting Page	199
Ending Page	210
Page Count	12
File Format	PDF
ISBN	9781605587110
DOI	10.1145/1629255.1629281
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-10-05
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Minimum distance Hybrid cpu/gpu algorithms Silhouette curves Gpu Nurbs Clearance analysis Closest point
Content Type	Text
Resource Type	Article

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