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A fast multigrid solver is presented for high-order accurate Stokes problems discretised by local discontinuous Galerkin (LDG) methods. The multigrid algorithm consists of a simple V-cycle, using an element-wise block Gauss-Seidel smoother.…

Numerical Analysis · Mathematics 2020-11-25 Robert Saye

Signed distance field (SDF) is a prominent implicit representation of 3D meshes. Methods that are based on such representation achieved state-of-the-art 3D shape reconstruction quality. However, these methods struggle to reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2020-10-21 Kacper Kania , Maciej Zięba , Tomasz Kajdanowicz

Program synthesis has emerged as a successful approach to the image parsing task. Most prior works rely on a two-step scheme involving supervised pretraining of a Seq2Seq model with synthetic programs followed by reinforcement learning (RL)…

Machine Learning · Computer Science 2021-06-16 Chenghui Zhou , Chun-Liang Li , Barnabas Poczos

Since the work of Kaligosi and Sanders (2006), it is well-known that Quicksort -- which is commonly considered as one of the fastest in-place sorting algorithms -- suffers in an essential way from branch mispredictions. We present a novel…

Data Structures and Algorithms · Computer Science 2016-06-27 Stefan Edelkamp , Armin Weiß

Dust properties, such as mass and porosity, impact planet formation directly. Understanding the time evolution of dust distribution across multiple properties requires numerical computation. However, available ways to calculate the…

Earth and Planetary Astrophysics · Physics 2026-05-19 Taichi K. Watanabe , Akimasa Kataoka

Algorithms for finding minimum or bounded vertex covers in graphs use a branch-and-reduce strategy, which involves exploring a highly imbalanced search tree. Prior GPU solutions assign different thread blocks to different sub-trees, while…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-29 Hussein Amro , Basel Fakhri , Amer E. Mouawad , Izzat El Hajj

This paper proposes a GPU-accelerated optimization framework for collision avoidance problems where the controlled objects and the obstacles can be modeled as the finite union of convex polyhedra. A novel collision avoidance constraint is…

Robotics · Computer Science 2024-06-12 Zeming Wu , Zhuping Wang , Hao Zhang

This work presents a fully GPU-accelerated algorithm for the polygonal mesh generator known as Polylla. Polylla is a tri-to-polygon mesh generator, which benefits from the half-edge data structure to manage any polygonal shape. The proposed…

Graphics · Computer Science 2024-03-25 Sergio Salinas-Fernández , Nancy Hitschfeld-Kahler , Roberto Carrasco

Nonlinear acceleration methods are powerful techniques to speed up fixed-point iterations. However, many acceleration methods require storing a large number of previous iterates and this can become impractical if computational resources are…

Machine Learning · Computer Science 2022-10-25 Huan He , Shifan Zhao , Ziyuan Tang , Joyce C Ho , Yousef Saad , Yuanzhe Xi

Neural networks have shown great potential in accelerating the solution of partial differential equations (PDEs). Recently, there has been a growing interest in introducing physics constraints into training neural PDE solvers to reduce the…

Machine Learning · Computer Science 2023-05-30 Xinquan Huang , Wenlei Shi , Qi Meng , Yue Wang , Xiaotian Gao , Jia Zhang , Tie-Yan Liu

Handling clustering problems are important in data statistics, pattern recognition and image processing. The mean-shift algorithm, a common unsupervised algorithms, is widely used to solve clustering problems. However, the mean-shift…

Computer Vision and Pattern Recognition · Computer Science 2021-12-30 Le You , Han Jiang , Jinyong Hu , Chorng Chang , Lingxi Chen , Xintong Cui , Mengyang Zhao

We present a fast algorithm for global rigid symmetry detection with approximation guarantees. The algorithm is guaranteed to find the best approximate symmetry of a given shape, to within a user-specified threshold, with very high…

Computational Geometry · Computer Science 2016-09-20 Simon Korman , Roee Litman , Shai Avidan , Alex Bronstein

Our main goal in this paper is to show that one can skip gradient computations for gradient descent type methods applied to certain structured convex programming (CP) problems. To this end, we first present an accelerated gradient sliding…

Optimization and Control · Mathematics 2016-09-19 Guanghui Lan , Yuyuan Ouyang

Hypergraph partitioning is a recurring NP-hard problem in engineering; its efficient solution at scale hinges on parallelism. This work proposes a GPU-centric algorithm for multi-level hypergraph partitioning aimed at a specific set of…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-21 Marco Ronzani , Cristina Silvano

Finding the convex hull is a fundamental problem in computational geometry. Quickhull is a fast algorithm for finding convex hulls. In this paper, we present VQhull, a fast parallel implementation of Quickhull that exploits vector…

Computational Geometry · Computer Science 2025-10-13 Thomas Koopman , Jordy Aaldering , Bernard van Gastel , Sven-Bodo Scholz

In this paper, we show that simple {Stochastic} subGradient Decent methods with multiple Restarting, named {\bf RSGD}, can achieve a \textit{linear convergence rate} for a class of non-smooth and non-strongly convex optimization problems…

Machine Learning · Computer Science 2016-04-01 Tianbao Yang , Qihang Lin

We present a convex hull algorithm that is accelerated on commodity graphics hardware. We analyze and identify the hurdles of writing a recursive divide and conquer algorithm on the GPU and divise a framework for representing this class of…

Computational Geometry · Computer Science 2015-03-20 Stanley Tzeng , John D. Owens

While well-known methods to list the intersections of either a list of segments or a complex polygon aim at achieving optimal time-complexity they often do so at the cost of memory comsumption and complex code. Real-life software…

Computational Geometry · Computer Science 2013-05-28 Jean Souviron

We present an algorithm for minimizing a sum of functions that combines the computational efficiency of stochastic gradient descent (SGD) with the second order curvature information leveraged by quasi-Newton methods. We unify these…

Machine Learning · Computer Science 2014-12-02 Jascha Sohl-Dickstein , Ben Poole , Surya Ganguli

In 1975, Valiant showed that Boolean matrix multiplication can be used for parsing context-free grammars (CFGs), yielding the asympotically fastest (although not practical) CFG parsing algorithm known. We prove a dual result: any CFG parser…

Computation and Language · Computer Science 2007-05-23 Lillian Lee