An evaluation of GPU filters for accelerating the 2D convex hull

Article Computer Science, Interdisciplinary Applications

POLYLLA: polygonal meshing algorithm based on terminal-edge regions

Sergio Salinas-Fernandez et al.

Summary: This paper presents an algorithm for generating a new type of polygonal mesh from triangulations. The algorithm, called Polylla, divides the process into three phases to label edges, build polygons from terminal-edge regions, and transform non-simple polygons into simple ones. The resulting mesh contains both convex and non-convex shapes. Compared to the commonly used Voronoi-based meshes, Polylla meshes have fewer polygons and a simpler and faster generation algorithm. The validity of Polylla meshes is confirmed through experiments and numerical performance comparisons with Voronoi meshes using the virtual element method.

ENGINEERING WITH COMPUTERS (2022)

添加到收藏夹

Article Computer Science, Theory & Methods

GPU Tensor Cores for Fast Arithmetic Reductions

Cristobal A. Navarro et al.

Summary: This article introduces a parallel algorithm for arithmetic reduction using GPU tensor cores, achieving faster performance and energy efficiency. Experimental results demonstrate that the proposed method outperforms standard GPU reduction and Nvidia's CUB library by approximately 3.2x and 2x, respectively, while maintaining low numerical error.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2021)

添加到收藏夹

Proceedings Paper Computer Science, Theory & Methods

Machine learning algorithm based on convex hull analysis

A. P. Nemirko et al.

Summary: This paper explores machine learning methods for automatic classification using computational geometry, proposing a proximity estimation method based on linear programming and showcasing experimental results in medical diagnostics. Efficiency comparison with other classifiers demonstrates the high efficiency of the proposed method.

14TH INTERNATIONAL SYMPOSIUM INTELLIGENT SYSTEMS (2021)

添加到收藏夹

Article Mathematics, Applied

A filtering technique for fast Convex Hull construction in R2

Hector Ferrada et al.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS (2020)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Parallelism in Randomized Incremental Algorithms

Guy E. Blelloch et al.

JOURNAL OF THE ACM (2020)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

A Preprocessing Technique for Fast Convex Hull Computation

Reham Alshamrani et al.

11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU

Gang Mei et al.

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING (2015)

添加到收藏夹

Article Computer Science, Software Engineering

CudaHull: Fast parallel 3D convex hull on the GPU

Ayal Stein et al.

COMPUTERS & GRAPHICS-UK (2012)

添加到收藏夹

An evaluation of GPU filters for accelerating the 2D convex hull

相关参考文献

导出引文

分享论文