OpenVX与三维渲染在多态GPU上的并行实现

针对图像处理与机器视觉以及三维图形渲染等所具有的大规模并行处理特征,通过充分利用面向图形图像处理的多态阵列架构(PAAG)处理器的可编程性以及灵活的并行处理方式,采用操作级并行与数据级并行相结合的并行化设计方法,实现了OpenVX中Kernel函数以及3D图形渲染.实验结果表明,在OpenVX标准图像处理Kernel函数以及图形渲染的并行实现中,采用PAAG处理器中的多指令多数据(MIMD)并行处理方式可以获得斜率为1的线性加速比,比传统图形处理器(GPU)中单指令多数据(SIMD)并行处理方式所得到的斜率值小于1的非线性加速比效率更高.     

Real‐time Depth of Field Rendering via Dynamic Light Field Generation and Filtering

We present a new algorithm for efficient rendering of high‐quality depth‐of‐field (DoF) effects. We start with a single rasterized view (reference view) of the scene, and sample the light field by warping the reference view to nearby views. We implement the algorithm using NVIDIA's CUDA to achieve parallel processing, and exploit the atomic operations to resolve visibility when multiple pixels warp to the same image location. We then directly synthesize DoF effects from the sampled light field. To reduce aliasing artifacts, we propose an image‐space filtering technique that compensates for spatial undersampling using MIP mapping. The main advantages of our algorithm are its simplicity and generality. We demonstrate interactive rendering of DoF effects in several complex scenes. Compared to existing methods, ours does not require ray tracing and hence scales well with scene complexity.     

超高分辨GIS信息显示技术

为解决海量 GIS 地图信息显示分辨率高、处理难度大等问题,研究了集群并行显示、WMS 服务、GIS渲染显示等技术,提出了以计算机集群并行计算为基础构建集群并行 GIS 拼接显示系统,采用 WMS 并行获取GIS数据信息、地图投影变换处理数据、OpenGL并行纹理渲染,进而实现GIS数据的超高分辨显示。实验结果表明,提出的集群并行GIS拼接显示系统可极大地提高地图显示分辨率、为海量GIS地图的超高分辨显示提供了可行的解决方案。     

Incremental Polygon Rendering on a SIMD Processor Array

We demonstrate how both area coherence and parallelism can be exploited in order to speed up rendering operations on a SIMD square array of processors. Our algorithms take advantage of the method of differences, in order to incrementally compute the values of a linear polynomial function at discrete intervals and thus implement area rendering operations efficiently. We discuss how filling of convex polygons, hidden surface elimination and smooth shading can be implemented on an N × N processor array that supports planar arithmetic, that is, arithmetic operations performed on N × N matrices in parallel for all matrix elements. A major attraction of the method we present is that it is based on a SIMD processor array; such machines are now recognised as highly general purpose given the wide range of applications successfully implemented on them.     

基于GPU的快速Level Set图像分割

水平集(1evel set)图像分割方法是图像分割中的一个重要方法，但是该算法的计算量大，往往不能达到实时处理的要求。给出了利用新一代的可编程图形处理器(GPU)实现level set的加速算法。首先介绍了如何在GPU上利用片元渲染程序进行网格化的线性运算和有限差分PDE计算，把level set方法的离散化算子映射到GPU上。由于以数据流处理方式的GPU的存储访问快，具有并行运算能力，同时level set算法演化的显示不再需要把数据从CPU传到GPU，因此较大地提高了算法速度与交互显示。文中实现并测试了一个与初始化状态独立的二维level set的算子用于图像分割，并对其运算结果和性能进行了比较，结果表明该方法具有更快的速度。     

计算机图形并行处理的研究与发展

本文概述了计算机图形并行处理研究的产生与发展,着重阐述了并行处理功能部件的研究和发展及多边形绘制、全局光照模型(光线跟踪与辐射度方法)、物理场数据与体介质数据绘制、动画、并行化图形标准等研究领域在并行处理方面的研究和发展.文中叙述了在这一领域的研究工作,并在最后展望了计算机图形并行处理的进一步发展方向.     

Dynamic load balancing for parallel polygon rendering

Using parallel processing for visualization speeds up computer graphics rendering of complex data sets. A parallel algorithm designed for polygon scan conversion and rendering is presented which supports fast rendering of highly complex data sets using advanced lighting models. Dedicated graphics rendering engines do not necessarily suit such data sets, although they can support real-time update of moderately complex scenes using simple lighting. Advantages to using a software-based approach include the feasibility of adding special rendering features to the program and the capability of integrating a parallel scientific application with a parallel graphics renderer. A new work decomposition strategy presented, called task adaptive, is based on dynamically partitioning the amount of computational work left at a given time. The algorithm uses a heuristic for dynamic task decomposition in which image space tasks are partitioned without requiring interruption of the partitioned processor. A sophisticated memory referencing strategy lets local memory access graphics data during rendering. This permits implementation of the algorithm on a distributed memory multiprocessor. An in-depth analysis of the overhead costs accompanying parallel processing shows where performance is adequate or could be improved     

Direct interval volume visualization

We extend direct volume rendering with a unified model for generalized isosurfaces, also called interval volumes, allowing a wider spectrum of visual classification. We generalize the concept of scale-invariant opacity—typical for isosurface rendering—to semi-transparent interval volumes. Scale-invariant rendering is independent of physical space dimensions and therefore directly facilitates the analysis of data characteristics. Our model represents sharp isosurfaces as limits of interval volumes and combines them with features of direct volume rendering. Our objective is accurate rendering, guaranteeing that all isosurfaces and interval volumes are visualized in a crack-free way with correct spatial ordering. We achieve simultaneous direct and interval volume rendering by extending preintegration and explicit peak finding with data-driven splitting of ray integration and hybrid computation in physical and data domains. Our algorithm is suitable for efficient parallel processing for interactive applications as demonstrated by our CUDA implementation.     

Real‐Time Concurrent Linked List Construction on the GPU

We introduce a method to dynamically construct highly concurrent linked lists on modern graphics processors. Once constructed, these data structures can be used to implement a host of algorithms useful in creating complex rendering effects in real time. We present a straightforward way to create these linked lists using generic atomic operations available in APIs such as OpenGL 4.0 and DirectX 11. We also describe several possible applications of our algorithm. One example uses per‐pixel linked lists for order‐independent transparency; as a consequence, we are able to directly implement fully programmable blending, which frees developers from the restrictions imposed by current graphics APIs. The second uses linked lists to implement real‐time indirect shadows.     

A kernel system for iconic image processing

We present a proposal for the design of a kernel system for iconic image processing operations and construct a virtual machine for image processing. The data structures and typical operations in the field of digital image processing are discussed. Furthermore, we give a formal definition of the operations and data objects required and describe one way to implement them by using the generic features of Ada.     

基于LOD的海量地形数据并行渲染技术

随着地球空间信息技术的发展,建立具有海量空间数据的大规模虚拟地形场景越来越重要. 然而,面对海量的地形数据,如何简化地形,提升绘制与渲染效率,是地形渲染的关键. 本文对LOD地形渲染技术、大规模数据集的分析与处理、并行计算等相关技术进行了研究,提出了基于LOD的海量地形数据并行渲染技术. 该技术首先使用LOD四叉树简化地形,其次结合多核CPU并行计算的方法提升效率,最后结合大规模数据调度策略,实现了海量地形数据的并行渲染,并分析对比了非并行和并行情况下的实验结果. 本文所取得的理论与技术方面的成果可为大规模场景渲染提供新的技术思路.     

Scalable Ray Tracing Using the Distributed FrameBuffer

Image‐ and data‐parallel rendering across multiple nodes on high‐performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, reducing bottlenecks incurred by the visualization and compositing is of key concern to reduce the overall simulation runtime. Moreover, prior algorithms have been designed to support either image‐ or data‐parallel rendering and impose restrictions on the data distribution, requiring different implementations for each configuration. In this paper, we introduce the Distributed FrameBuffer, an asynchronous image‐processing framework for multi‐node rendering. We demonstrate that our approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distributions. By building on this framework, we extend the open‐source ray tracing library OSPRay with a data‐distributed API, enabling its use in data‐distributed and in situ visualization applications.     

Parallel implementing OpenGL on PVM

A 3D polygon rendering system conforming to the specification of OpenGL is implemented on a PVM (parallel virtual machine). The system is targeted to a low speed network of low cost serial computers. In our parallel rendering algorithm, image space is decomposed to exactly the number of regions equal to the number of processors which reduces the volume of communication and the polygons needed to be rendered more than once on separate renderers. We also propose a transmission scheme that distributes the passing of data throughout the whole process of rendering. Taking advantage of frame-to-frame coherence, load balancing is achieved by decomposing the image space unequally so that the workloads in each space region are proportional to the processing power of the corresponding renders. Distribution of workload and processing power that is volatile during rendering are obtained with linear prediction from statistics of previous frames. The system is practical and scalable for moderate number of processors.     

Application of a parallel pattern processor to remote sensing

This paper describes application techniques of satellite remote sensing using a newly developed interactive digital image processing system, where a parallel pattern processor performs characteristic roles. The pattern processor can execute several image processing functions at high speed, which are frequently used in remote sensing studies; affine transformation for geometric correction of LANDSAT MSS data to implement a satellite image database, maximum likelihood estimation for land cover classification, and pixelwise operations for change detection, etc.

These application results indicate that the developed interactive image processing system is sufficiently effective to process remote-sensed data.     

并行绘制系统Chromium中的3D模型数据压缩

网络带宽不足严重限制了Chromium等并行图形绘制系统渲染巨型几何场景的速度。通过对网络传输中的几何数据进行无损压缩,提出了一种能有效缓解网络负荷的方法。该方法可以很容易地实现不同算法对特定几何数据的压缩。实现了ZLib和哈夫曼算法对Chromium系统的压缩,测试了系统对10类OpenGL应用程序的加速比和压缩比,以及在4种配置环境下的并行运行效果。使用ZLib算法时,测试程序的运行速度都有不同程度的提高,最高提升3倍;数据压缩比平均在5.0以上,最高为30;并行绘制加速比在单服务器数目下最高。ZLib算法整体表现良好,能有效减少网络通信量。     

一种高度并行的多任务并行绘制系统结构

随着计算机图形技术的实用化，需要构造更逼真、更精细的三维复杂场景，其数据规模日益膨胀，加上对场景的实时交互的要求也越来越高，人们对多屏幕高分辨率显示的需求与日俱增，迫切需要一种针对大规模复杂场景的多任务并行图形绘制系统。本文介绍了一种适用于大规模复杂场景的高度并行的多任务多屏幕并行图形绘制系统的体系结构，支持图形任务的并行化处理和多屏幕显示。该系统结构将几何计算任务与图形绘制任务相分离，分剐进行并行化处理，在计算节点按绘制对象类型对任务进行分类以便于并行计算和任务分配，在绘制节点对各个小块屏幕图形进行并行合成。实验测试结果表明，该系统结构对多任务具有较好的并行效率和可扩展性，能够充分利用系统的并行计算资源，达到较好的绘制效果。     

A sorting classification of parallel rendering

We describe a classification scheme that we believe provides a more structured framework for reasoning about parallel rendering. The scheme is based on where the sort from object coordinates to screen coordinates occurs, which we believe is fundamental whenever both geometry processing and rasterization are performed in parallel. This classification scheme supports the analysis of computational and communication costs, and encompasses the bulk of current and proposed highly parallel renderers - both hardware and software. We begin by reviewing the standard feed-forward rendering pipeline, showing how different ways of parallelizing it lead to three classes of rendering algorithms. Next, we consider each of these classes in detail, analyzing their aggregate processing and communication costs, possible variations, and constraints they may impose on rendering applications. Finally, we use these analyses to compare the classes and identify when each is likely to be preferable     

Instant Visibility

We present an online occlusion culling system which computes visibility in parallel to the rendering pipeline. We show how to use point visibility algorithms to quickly calculate a tight potentially visible set (PVS) which is valid for several frames, by shrinking the occluders used in visibility calculations by an adequate amount. These visibility calculations can be performed on a visibility server, possibly a distinct computer communicating with the display host over a local network. The resulting system essentially combines the advantages of online visibility processing and region-based visibility calculations, allowing asynchronous processing of visibility and display operations. We analyze two different types of hardware-based point visibility algorithms and address the problem of bounded calculation time which is the basis for true real-time behavior. Our results show reliable, sustained 60 Hz performance in a walkthrough with an urban environment of nearly 2 million polygons, and a terrain flyover.     

Efficient Geometry Compression for GPU-based Decoding in Realtime Terrain Rendering

We present a geometry compression scheme for restricted quadtree meshes and use this scheme for the compression of adaptively triangulated digital elevation models (DEMs). A compression factor of 8–9 is achieved by employing a generalized strip representation of quadtree meshes to incrementally encode vertex positions. In combination with adaptive error-controlled triangulation, this allows us to significantly reduce bandwidth requirements in the rendering of large DEMs that have to be paged from disk. The compression scheme is specifically tailored for GPU-based decoding, since it minimizes dependent memory access operations. We can thus trade CPU operations and CPU–GPU data transfer for GPU processing, resulting in twice faster streaming of DEMs from main memory into GPU memory. A novel storage format for decoded DEMs on the GPU facilitates a sustained rendering throughput of about 300 million triangles per second. Due to these properties, the proposed scheme enables scalable rendering with respect to the display resolution independent of the data size. For a maximum screen-space error below 1 pixel it achieves frame rates of over 100 fps, even on high-resolution displays. We validate the efficiency of the proposed method by presenting experimental results on scanned elevation models of several hundred gigabytes.     

FPGA-based architecture for hardware compression/decompression of wide format images

In this article, we present a popular lossless compression/decompression algorithm, GZIP, and the study to implement it on an FPGA-based architecture, the ADM-XRC board from ALPHA DATA parallel system ltd. The algorithm is lossless, and applied to “bi-level” images of large size (A0 format). It ensures a minimum compression rate for the images we are considering. It aims to decrease storage requirements and transfer times, which are critical for wide format printing systems. In a wide format document industry, raster data are most of time processed in an uncompressed format, in order to apply processing (P) before printing (p). An example of a copy chain is composed of scanner, set of processing operations, storage, link and printer. We propose to use a compressed format as the new data-flow representation to improve the performances of the printing system. For example, the compression (C) is applied as soon as the data are produced by the scanner, and decompression (D) is performed at the last stage, before printing. The set of processing is applied to compressed images. The proposed architecture for the compressor is based on a hash table and the decompressor is based on a parallel decoder of the Huffman codes. We implemented the proposed architecture for compression and decompression algorithms on FPGA Xilinx Virtex XCV 400.