TY - GEN

T1 - Hardware-assisted natural neighbor interpolation

AU - Fan, Quanfu

AU - Efrat, Alon

AU - Koltun, Vladlen

AU - Krishnan, Shankar

AU - Venkatasubramanian, Suresh

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Natural neighbor interpolation is a weighted average interpolation method that is based on Voronoi tessellation. In this paper, we present and implement an algorithm for performing natural neighbor interpolation using graphics hardware. Unlike traditional software-based approaches that process one query at a time, we develop a scheme that computes the entire scalar field induced by natural neighbor interpolation, at which point a query is a trivial array lookup, arid range queries over the field are easy to perform. Our approach is faster than the best known software implementations and makes use of general purpose stream programming capabilities of current graphics cards. We also present a simple scheme that requires no advanced graphics capabilities and can process natural neighbor queries faster than existing software-based approaches. Finally, recognizing the limitation incurred by the bounded size of graphics frame buffers, we propose a sub-division approach that allows performing queries locally in a subdivision of the input domain. This approach can reduce to a negligibly small degree (< 1%) the loss of precision caused by the naive scaling method while still processing queries faster than the software-based approaches when the number of sites is large.

AB - Natural neighbor interpolation is a weighted average interpolation method that is based on Voronoi tessellation. In this paper, we present and implement an algorithm for performing natural neighbor interpolation using graphics hardware. Unlike traditional software-based approaches that process one query at a time, we develop a scheme that computes the entire scalar field induced by natural neighbor interpolation, at which point a query is a trivial array lookup, arid range queries over the field are easy to perform. Our approach is faster than the best known software implementations and makes use of general purpose stream programming capabilities of current graphics cards. We also present a simple scheme that requires no advanced graphics capabilities and can process natural neighbor queries faster than existing software-based approaches. Finally, recognizing the limitation incurred by the bounded size of graphics frame buffers, we propose a sub-division approach that allows performing queries locally in a subdivision of the input domain. This approach can reduce to a negligibly small degree (< 1%) the loss of precision caused by the naive scaling method while still processing queries faster than the software-based approaches when the number of sites is large.

UR - http://www.scopus.com/inward/record.url?scp=32144460834&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=32144460834&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:32144460834

SN - 0898715962

SN - 9780898715965

T3 - Proceedings of the Seventh Workshop on Algorithm Engineering and Experiments and the Second Workshop on Analytic Algorithms and Combinatorics

SP - 111

EP - 120

BT - Proceedings of the Seventh Workshop on Algorithm Engineering and Experiments and the Second Workshop on Analytic Algorithms and Combinatorics

A2 - Demetrescu, C.

A2 - Sedgewick, R.

A2 - Tamassia, R.

T2 - Seventh Workshop on Algorithm Engineering and Experiments and the Second Workshop on Analytic Algorithms and Combinatorics

Y2 - 22 January 2005 through 22 January 2005

ER -