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Rahul Khardekar

dblp:57/5306 · DBLP profile ↗
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7ranked-venue papers
3as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 7 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
3 papers
Geometric modeling and processing · 70% Computational fabrication · 23% Rendering · 7%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
GPUs and heterogeneous computing · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › computer-aided design › computer-aided geometric design › NURBS modeling
NURBS surface modeling
0.112009
Performing Efficient NURBS Modeling Operations on the GPU · IEEE Trans. Vis. Comput. Graph. 2009
Geometric modeling and processing › surface processing
surface intersection
0.112009
Performing Efficient NURBS Modeling Operations on the GPU · IEEE Trans. Vis. Comput. Graph. 2009
Computational fabrication › mechanical design
mold design
0.112006
Finding feasible mold parting directions using graphics hardware · Comput. Aided Des. 2006
GPUs and heterogeneous computing › GPU computing › GPGPU acceleration
GPU acceleration of geometric computation
0.012009
Performing Efficient NURBS Modeling Operations on the GPU · IEEE Trans. Vis. Comput. Graph. 2009
GPUs and heterogeneous computing
GPU computing
0.012009
Optimized GPU evaluation of arbitrary degree NURBS curves and surfaces · Comput. Aided Des. 2009
Rendering
GPU rendering
0.012006
Finding feasible mold parting directions using graphics hardware · Comput. Aided Des. 2006

Methods — techniques the papers use, named apart from their topics

programmable fragment processor · 0.2NURBS evaluation · 0.2graphics hardware · 0.1
YearPublicationVenuePosition
2009 Efficient computation of a near-optimal primary parting line
abstract
In injection molding, a flat parting surface that is normal to the mold parting direction achieves the best mold alignment with the least cost. However, for complex parts, parting surfaces that consist of a number of planes are necessary. In this paper, we provide an algorithm to find a near-optimal parting surface as a series of planes that intersect the boundary of the part.We form a continuous band of triangles on the part boundary that are parallel to the parting direction within a tolerance and perform vertical trapezoidation of the band. We can then find a set of planes that intersect vertical lines in the trapezoidation. We use a linear program to keep the planes normal to the parting direction.
Rahul Khardekar, Sara McMains
Symposium on Solid and Physical Modeling1
2009 Optimized GPU evaluation of arbitrary degree NURBS curves and surfaces
Adarsh Krishnamurthy, Rahul Khardekar, Sara McMains
Comput. Aided Des.2
2009 Performing Efficient NURBS Modeling Operations on the GPU
abstract
We present algorithms for evaluating and performing modeling operations on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for retessellation. Our GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates. We also extend our surface-surface intersection algorithm to evaluate self-intersections in NURBS surfaces.
Adarsh Krishnamurthy, Rahul Khardekar, Sara McMains, Kirk Haller, Gershon Elber
IEEE Trans. Vis. Comput. Graph.2
2008 Performing efficient NURBS modeling operations on the GPU
abstract
We present algorithms for evaluating and performing modeling operatyons on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for re-tessellation. We also present a GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces that can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates.
Adarsh Krishnamurthy, Rahul Khardekar, Sara McMains, Kirk Haller, Gershon Elber
Symposium on Solid and Physical Modeling2
2007 Direct evaluation of NURBS curves and surfaces on the GPU
abstract
This paper presents a new method to evaluate and display trimmed NURBS surfaces using the Graphics Processing Unit (GPU). Trimmed NURBS surfaces, the de facto standard in commercial 3D CAD modeling packages, are currently tessellated into triangles before being sent to the graphics card for display since there is no native hardware support for NURBS. Previous GPU-based NURBS display methods relied on first approximating the NURBS patches with lower degree Bezier patches before evaluation. Our method uses a GPU fragment program to evaluate the surface point coordinates of the original NURBS patch directly, from the control points and knot vectors stored as textures in graphics memory. This evaluated surface is trimmed during display using a dynamically generated trim-texture calculated via alpha blending. The implementation incorporates dynamic Level of Detail (LOD) for real-time interaction at different resolutions of the NURBS surfaces. We obtain rendering speeds at least one order of magnitude faster than evaluation using the CPU.
Adarsh Krishnamurthy, Rahul Khardekar, Sara McMains
Symposium on Solid and Physical Modeling2
2006 Finding feasible mold parting directions using graphics hardware
Rahul Khardekar, Greg Burton, Sara McMains
Comput. Aided Des.1
2005 Finding feasible mold parting directions using graphics hardware
abstract
We present new programmable graphics hardware accelerated algorithms to test the castability of geometric parts and assist with part redesign. These algorithms efficiently identify and graphically display undercuts and minimum and insufficient draft angles. Their running times grow only linearly with respect to the number of facets in the solid model, making them efficient subroutines for our algorithms that test whether a tessellated CAD model can be manufactured in a two-part mold. We have developed and implemented two such algorithms to choose candidate directions to test for castability using accessibility analysis and Gauss maps. The efficiency of these algorithms lies in that they identify groups of candidate directions such that if any one direction in the group is not castable, none are, or if any one is castable, all are. We examine trade-offs between the algorithms' speed, accuracy, and whether they guarantee that a castable direction will be found for a part if one exists.
Rahul Khardekar, Greg Burton, Sara McMains
Symposium on Solid and Physical Modeling1