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检索条件"主题词=GPU algorithms"

共 28 条记录，以下是11-20 订阅

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Real-time Rendering of Large-scale Terrain based on gpu

Real-time Rendering of Large-scale Terrain based on GPU

引用

4th IEEE Conference on Industrial Electronics and Applications

作者： Zhang, Yanyan Huang, Qitao Han, Junwei Harbin Inst Technol Sch Mechatron Engn Harbin 150006 Heilongjiang Pr Peoples R China

ISBN: (纸本)9781424427994

For efficient visualization, storage and management of massive datasets in current large-scale terrain rendering system, a real-time rendering algorithm of large-scale terrain based on gpu (Graphic Processing Unit) is proposed. The algorithm is an out-of-core supported aggregated LOD (Level of Detail) rendering method and focuses on the use of gpus' ability in the computation and programmability. The two-ratio filtering simplification method and quadtree-based chunk hierarchy are used to generate a simple and regular chunk structure for view-dependent LOD visualization. Based on this structure, a gpu-oriented data compression strategy is given for reducing data transfer bandwidth and storage consumption;a template-based triangle stripification method is used for optimizing visualization efficiency and generating a conforming terrain without cracks. Besides the management strategy of massive datasets which is based on a two-level caching mechanism makes the algorithm breakthrough the hardware limitation and realize the out-of-core rendering. During the typical fly-over for large-scale datasets, a very high frame rate can be guaranteed by the algorithm.

关键词： Terrain rendering gpu algorithms View-dependent level of detail Terrain data compression Out-of-core

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Deep opacity maps

Deep opacity maps

引用

29th Annual Conference of the European-Association-for-Computer-Graphics

作者： Yuksel, Cem Keyser, John Texas A&M Univ Dept Comp Sci College Stn TX 77843 USA

We present a new method for rapidly computing shadows from semi-transparent objects like hair. Our deep opacity maps method extends the concept of opacity shadow maps by using a depth map to obtain a per pixel distribution of opacity layers. This approach eliminates the layering artifacts of opacity shadow maps and requires far fewer layers to achieve high quality shadow computation. Furthermore, it is faster than the density clustering technique, and produces less noise with comparable shadow quality. We provide qualitative comparisons to these previous methods and give performance results. Our algorithm is easy to implement, faster, and more memory efficient, enabling us to generate high quality hair shadows in real-time using graphics hardware on a standard PC.

关键词： shadow maps semi-transparent shadows hair shadows real-time shadows gpu algorithms

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Fast gpu ray tracing of dynamic meshes using geometry images

Fast GPU ray tracing of dynamic meshes using geometry images

引用

32nd Graphics Interface Conference

作者： Carr, Nathan A. Hoberock, Jared Crane, Keenan Hart, John C. Adobe Corp. University of Illinois Urbana-Champaign United States

ISBN: (纸本)1568813082

Using the gpu to accelerate ray tracing may seem like a natural choice due to the highly parallel nature of the problem. However, determining the most versatile gpu data structure for scene storage and traversal is a challenge. In this paper, we introduce a new method for quick intersection of triangular meshes on the gpu. The method uses a threaded bounding volume hierarchy built from a geometry image, which can be efficiently traversed and constructed entirely on the gpu. This acceleration scheme is highly competitive with other gpu ray tracing methods, while allowing for both dynamic geometry and an efficient level of detail scheme at no extra cost.

关键词： ray tracing gpu algorithms geometry images mesh parameterization

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gpu-accelerated Adaptively Sampled Distance Fields

GPU-accelerated Adaptively Sampled Distance Fields

引用

IEEE International Conference on Shape Modeling and Applications

作者： Bastos, Thiago Celes, Waldemar Tecgraf - Computer Graphics Technology Group Department of Computer Science PUC-Rio Brazil

ISBN: (纸本)9781424422609

Adaptively Sampled Distance Fields (ADFs) are volumetric shape representations that support a broad range of applications in the areas of computer graphics, computer vision and physics. ADFs are especially beneficial for representing shapes with features at very diverse scales. In this paper, we propose a strategy to represent and reconstruct ADFs on modem graphics hardware (gpus). We employ a 3D hashing scheme to store the underlying data structure and try to balance the tradeoff between memory requirements and reconstruction efficiency. To render ADFs on gpu, we use a general-purpose ray-casting technique based on sphere tracing, which guarantees the reconstruction of fine details. We also present a way to overcome the C-1 discontinuities inherent to ADFs and efficiently reconstruct smooth surface normals across cell boundaries. The effectiveness of our proposal is demonstrated for isosurface rendering and morphing.

关键词： ADFs gpu algorithms implicit surface rendering

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Dual scattering approximation for fast multiple scattering in hair

Dual scattering approximation for fast multiple scattering i...

引用

ACM SIGGRAPH Conference 2008

作者： Zinke, Arno Yuksel, Cem Weber, Andreas Keyser, John Univ Bonn Inst Informat 2 D-5300 Bonn Germany Texas A&M Univ Dept Comp Sci College Stn TX 77843 USA

When rendering light colored hair, multiple fiber scattering is essential for the right perception of the overall hair color. In this context, we present a novel technique to efficiently approximate multiple fiber scattering for a full head of human hair or a similar fiber based geometry. In contrast to previous ad-hoc approaches, our method relies on the physically accurate concept of the Bidirectional Scattering Distribution Functions and gives physically plausible results with no need for parameter tweaking. We show that complex scattering effects can be approximated very well by using aggressive simplifications based on this theoretical model. When compared to unbiased Monte-Carlo path tracing, our approximations preserve photo-realism in most settings but with rendering times at least two-orders of magnitude lower. Time and space complexity are much lower compared to photon mapping-based techniques and we can even achieve realistic results in real-time on a standard PC with consumer graphics hardware.

关键词： hair rendering multiple scattering gpu algorithms

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AUTOENCODER versus PRE-TRAINED CNN NETWORKS: Deep-Features applied to accelerate computationally expensive object detection in real-time video streams 4

AUTOENCODER versus PRE-TRAINED CNN NETWORKS: Deep-Features a...

引用

Conference on Target and Background Signatures IV

作者： Iyer, Vasanth Aved, Alexander Howlett, Todd B. Carlo, Jeffrey T. Abayowa, Bernard Troy Univ Comp Sci Dept Troy AL 36082 USA Air Force Res Labs Rome NY USA Air Force Res Labs Wright Patterson AFB OH USA

ISBN: (数字)9781510621725

ISBN: (纸本)9781510621725

Traditional event detection from video frames are based on a batch or offline based algorithms: it is assumed that a single event is present within each video, and videos are processed, typically via a pre-processing algorithm which requires enormous amounts of computation and takes lots of CPU time to complete the task. While this can be suitable for tasks which have specified training and testing phases where time is not critical, it is entirely unacceptable for some real-world applications which require a prompt, real-time event interpretation on time. With the recent success of using multiple models for learning features such as generative adversarial autoencoder (GANS), we propose a two-model approach for real-time detection. Like GANs which learns the generative model of the dataset and further optimizes by using the discriminator which learn per sample difference between generated images. The proposed architecture uses a pre-trained model with a large dataset which is used to boost weekly labeled instances in parallel with deep-layers for the small aerial targets with a fraction of the computation time for training and detection with high accuracy. We emphasize previous work on unsupervised learning due to overheads in training labeled data in the sensor domain.

关键词： Autoencode Pre-trained Model Real-time video streaming Aerial Images Deep Learning Event Detection gpu algorithms

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In-memory k Nearest Neighbor gpu-based Query Processing 6

In-memory k Nearest Neighbor GPU-based Query Processing

引用

6th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM)

作者： Velentzas, Polychronis Vassilakopoulos, Michael Corral, Antonio Univ Thessaly Dept Elect & Comp Engn Data Structuring & Eng Lab Volos Greece Univ Almeria Dept Informat Almeria Spain

ISBN: (纸本)9789897584251

The k Nearest Neighbor (k-NN) algorithm is widely used for classification in several application domains (medicine, economy, entertainment, etc.). Let a group of query points, for each of which we need to compute the k-NNs within a reference dataset to derive the dominating feature class. When the reference points volume is extremely big, it can be proved challenging to deliver low latency results. Furthermore, when the query points are originating from streams, the need for new methods arises to address the computational overhead. We propose and implement two in-memory gpu-based algorithms for the k-NN query, using the CUDA API and the Thrust library. The first one is based on a Brute Force approach and the second one is using heuristics to minimize the reference points near a query point. We also present an extensive experimental comparison against existing algorithms, using synthetic and real datasets. The results show that both of our algorithms outperform these algorithms, in terms of execution time as well as total volume of in-memory reference points that can be handled.

关键词： Nearest Neighbors gpu algorithms Spatial Query In-memory Processing Parallel Computing

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Exploring the Design Space of Static and Incremental Graph Connectivity algorithms on gpus 20

Exploring the Design Space of Static and Incremental Graph C...

引用

ACM International Conference on Parallel Architectures and Compilation Techniques (PACT)

作者： Hong, Changwan Dhulipala, Laxman Shun, Julian MIT CSAIL Cambridge MA 02139 USA CMU Pittsburgh PA USA

ISBN: (纸本)9781450380751

Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. gpus are an ideal platform for graph algorithms due to their high peak performance and memory bandwidth. While there exist several gpu connectivity algorithms in the literature, many design choices have not yet been explored. In this paper, we explore various design choices in gpu connectivity algorithms, including sampling, linking, and tree compression, for both the static as well as the incremental setting. Our various design choices lead to over 300 new gpu implementations of connectivity, many of which outperform state-of-the-art. We present an experimental evaluation, and show that we achieve an average speedup of 2.47x speedup over existing static algorithms. In the incremental setting, we achieve a throughput of up to 48.23 billion edges per second. Compared to state-of-the-art CPU implementations on a 72-core machine, we achieve a speedup of 8.26-14.51x for static connectivity and 1.85-13.36x for incremental connectivity using a Tesla V100 gpu.

关键词： Connected components Graph algorithms gpu algorithms Spanning forest

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Accelerated Discovery of Discrete M-Clusters/Outliers on the Raster Plane Using Graphical Processing Units

Accelerated Discovery of Discrete M-Clusters/Outliers on the...

引用

9th International Conference on Computational Science

作者： Trefftz, Christian Szakas, Joseph Majdandzic, Igor Wolffe, Gregory Grand Valley State Univ Sch Comp Allendale MI 49401 USA Univ Maine Comp Informat Syst Dept Augusta GA 04330 USA

ISBN: (纸本)9783642019692

This paper presents two discrete computational geometry algorithms designed for execution on Graphics Processing Units (gpus). The algorithms are parallelized versions of sequential algorithms intended for application in geographical data mining. The first algorithm finds clusters of in points, called m-clusters, in the rasterized plane. The second algorithm complements the first by identifying outliers, those points which are not members of any m-clusters. The use of a raster representation of coordinates provides an ideal data stream environment for efficient gpu utilization. The parallel algorithms have low memory demands, and require only a limited amount of inter-process communication. Initial performance analysis indicates the algorithms are scalable, both in problem size and in the number of seeds, and significantly outperform commercial implementations.

关键词： gpu algorithms Geographical data mining CUDA programming

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Wave particles 07

Wave particles

引用

ACM SIGGRAPH 2007 Conference

作者： Yuksel, Cent House, Donald H. Keyser, John Texas A&M Univ College Stn TX 77843 USA Texas A&M Univ Visualizat Lab College Stn TX 77843 USA

ISBN: (纸本)9781450378369

We present a new method for the real-time simulation of fluid surface waves and their interactions with floating objects. The method is based on the new concept of wave particles, which offers a simple, fast, and unconditionally stable approach to wave simulation. We show how graphics hardware can be used to convert wave particles to a height field surface, which is warped horizontally to account for local wave-induced flow. The method is appropriate for most fluid simulation situations that do not involve significant global flow. It is demonstrated to work well in constrained areas, including wave reflections off of boundaries, and in unconstrained areas, such as an ocean surface. Interactions with floating objects are easily integrated by including wave forces on the objects and wave generation due to object motion. Theoretical foundations and implementation details are provided, and experiments demonstrate that we achieve plausible realism. Timing studies show that the method is scalable to allow simulation of wave interaction with several hundreds of objects at real-time rates.

关键词： wave particles waves real-time simulation fluid-object interaction gpu algorithms

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