787 research outputs found
Computing Three-dimensional Constrained Delaunay Refinement Using the GPU
We propose the first GPU algorithm for the 3D triangulation refinement
problem. For an input of a piecewise linear complex and a
constant , it produces, by adding Steiner points, a constrained Delaunay
triangulation conforming to and containing tetrahedra mostly of
radius-edge ratios smaller than . Our implementation of the algorithm shows
that it can be an order of magnitude faster than the best CPU algorithm while
using a similar amount of Steiner points to produce triangulations of
comparable quality
A parallel algorithm for Delaunay triangulation of moving points on the plane
Delaunay Triangulation(DT) is one of the important geometric problems that is
used in various branches of knowledge such as computer vision, terrain
modeling, spatial clustering and networking. Kinetic data structures have
become very important in computational geometry for dealing with moving
objects. However, when dealing with moving points, maintaining a dynamically
changing Delaunay triangulation can be challenging. So, In this case, we have
to update triangulation repeatedly. If points move so far, it is better to
rebuild the triangulation. One approach to handle moving points is to use an
incremental algorithm. For the case that points move slowly, we can give a
faster algorithm than rebuilding it. Furthermore, sequential algorithms can be
computationally expensive for large datasets. So, one way to compute as fast as
possible is parallelism. In this paper, we propose a parallel algorithm for
moving points. we propose an algorithm that divides datasets into equal
partitions and give every partition to one block. Each block satisfay the
Delaunay constraints after each time step and uses delete and insert algorithms
to do this. We show this algorithm works faster than serial algorithms
Parallel constrained Delaunay triangulation
In this paper we propose a new GPU method able to compute the 2D constrained Delaunay triangulation of a planar straight line graph consisting of points and segments. The method is based on an incremental insertion, taking special care to avoid conflicts during concurrent insertion of points into the triangulation and concurrent edge flips.Ministerio de Ciencia e Innovació
One machine, one minute, three billion tetrahedra
This paper presents a new scalable parallelization scheme to generate the 3D
Delaunay triangulation of a given set of points. Our first contribution is an
efficient serial implementation of the incremental Delaunay insertion
algorithm. A simple dedicated data structure, an efficient sorting of the
points and the optimization of the insertion algorithm have permitted to
accelerate reference implementations by a factor three. Our second contribution
is a multi-threaded version of the Delaunay kernel that is able to concurrently
insert vertices. Moore curve coordinates are used to partition the point set,
avoiding heavy synchronization overheads. Conflicts are managed by modifying
the partitions with a simple rescaling of the space-filling curve. The
performances of our implementation have been measured on three different
processors, an Intel core-i7, an Intel Xeon Phi and an AMD EPYC, on which we
have been able to compute 3 billion tetrahedra in 53 seconds. This corresponds
to a generation rate of over 55 million tetrahedra per second. We finally show
how this very efficient parallel Delaunay triangulation can be integrated in a
Delaunay refinement mesh generator which takes as input the triangulated
surface boundary of the volume to mesh
Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded Devices
For many applications in low-power real-time robotics, stereo cameras are the
sensors of choice for depth perception as they are typically cheaper and more
versatile than their active counterparts. Their biggest drawback, however, is
that they do not directly sense depth maps; instead, these must be estimated
through data-intensive processes. Therefore, appropriate algorithm selection
plays an important role in achieving the desired performance characteristics.
Motivated by applications in space and mobile robotics, we implement and
evaluate a FPGA-accelerated adaptation of the ELAS algorithm. Despite offering
one of the best trade-offs between efficiency and accuracy, ELAS has only been
shown to run at 1.5-3 fps on a high-end CPU. Our system preserves all
intriguing properties of the original algorithm, such as the slanted plane
priors, but can achieve a frame rate of 47fps whilst consuming under 4W of
power. Unlike previous FPGA based designs, we take advantage of both components
on the CPU/FPGA System-on-Chip to showcase the strategy necessary to accelerate
more complex and computationally diverse algorithms for such low power,
real-time systems.Comment: 8 pages, 7 figures, 2 table
Characterization and surface reconstruction of objects in tomographic images of composite materials
Dissertação para obtenção do Grau de Mestre em
Engenharia InformáticaIn the scope of the project Tomo-GPU supported by FCT / MCTES the aim is to build
an interactive graphical environment that allows a Materials specialist to define their
own programs for analysis of 3D tomographic images. This project aims to build a tool
to characterize and investigate the identified objects, where the user can define search criteria such as size, orientation, bounding boxes, among others. All this processing will be done on a desktop computer equipped with a graphics card with some processing power.
On the proposed solution the modules for characterizing objects, received from the
identification phase, will be implemented using some existing software libraries, most
notably the CGAL library. The characterization modules with bigger execution times will be implemented using OpenCL and GPUs. With this work the characterization and reconstruction of objects and their research can now be done on conventional machines, using GPUs to accelerate the most time-consuming computations. After the conclusion of this thesis, new tools that will help to improve the current development cycle of new materials will be available for Materials Science specialists
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