convex hull 관련 논문

1. A Parallel Algorithm for Convex Hull Computations: This paper discusses the application of convex hull computations in various fields like computer graphics, computer-aided design, image processing, robotics, and surrogate modeling. Although it doesn't provide specific details on the algorithm, it emphasizes the importance of convex hull computations in a wide range of disciplines.

2. ConcurrentHull: A Fast Parallel Computing Approach to the Convex Hull: This study introduces a novel pruning-based approach for finding the convex hull set for 2D and 3D datasets using parallel algorithms. The method combines pruning, divide and conquer, and parallel computing, making it suitable for distributed computing environments.

3. Accelerating the Convex Hull Computation with a Parallel GPU-Based Adaptation of Heaphull: This research proposes a parallel GPU-based adaptation of the heaphull algorithm, a state-of-the-art CPU algorithm for convex hull computation. The process involves an efficient filtering stage before the actual convex hull computation, highlighting the use of parallel processing to enhance performance.

4. CudaHull: Fast Parallel 3D Convex Hull on the GPU: This paper presents a novel parallel algorithm for computing the convex hull of a set of points in 3D using the CUDA programming model. The method is based on the QuickHull approach and involves constructing an initial tetrahedron using four extreme points, discarding internal points, and iteratively distributing external points to the four faces.

5. Parallel Implementations for Determining the 2D Convex Hull: This paper showcases the value of analyzing a serial implementation for understanding an application's nature. It describes a parallel implementation of a divide-and-conquer algorithm for determining the convex hull of a set of 2D points, building upon an earlier serial implementation.

These papers collectively demonstrate the diversity and innovation in approaches to parallel processing for convex hull computations, spanning different dimensions (2D and 3D) and employing various techniques like pruning, divide and conquer, and GPU-based adaptations.