Distributed parallel rendering provides a valuable way to navigate large-scale scenes. However, previous works typically focused on outputting ultra-high-resolution images. In this paper, we target ...on improving the interactivity of navigation and propose a large-scale scene navigation method, GuideRender, based on multi-modal view frustum movement prediction. Given previous frames, user inputs and object information, GuideRender first extracts frames, user inputs and objects features spatially and temporally using the multi-modal extractor. To obtain effective fused features for prediction, we introduce an attentional guidance fusion module to fuse these features of different domains with attention. Finally, we predict the movement of the view frustum based on the attentional fused features and obtain its future state for loading data in advance to reduce latency. In addition, to facilitate GuideRender, we design an object hierarchy hybrid tree for scene management based on the object distribution and hierarchy, and an adaptive virtual sub-frustum decomposition method based on the relationship between the rendering cost and the rendering node capacity for task decomposition. Experimental results show that GuideRender outperforms baselines in navigating large-scale scenes. We also conduct a user study to show that our method satisfies the navigation requirements in large-scale scenes.
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Leading-edge supercomputers, such as the K computer and Fugaku, have been designed to achieve the highest computational performance possible as well as to tackle “Grand Challenge” class of ...simulations with unprecedented scale. This significant increase in the simulation scale has directly imposed a pressure on the entire end-to-end simulation workflow, which includes the pre- and post-processing such as the visualization. During the simulation code development and refinement process in such HPC environment, a variety of auxiliary computational systems with different hardware and software configurations can be employed for the post-processing activities. Therefore, a visualization application capable of running on such heterogeneous hardware environment, which uses common visualization pipeline workflow and unified abstract representation becomes highly valuable. In this paper, we present a visualization framework, named HIVE (Heterogeneously Integrated Visual-analytics Environment), designed to meet these requirements by using lightweight and cross-platform Lua scripting language for describing the desired visualization pipeline workflow, which was named as “Visualization Scene” script. Different visualization pipeline functionality modules such as data loading, rendering, and image compositing written in C/C++ programming language can be utilized via Lua by using its binding functionality. HIVE has currently integrated some cross-platform modules, and is capable of running on different hardware systems, ranging from x86 laptops to SPARC64 based supercomputers with tens of thousands of processors. As a future direction, we expect to include the supercomputers using Arm-based Fujitsu A64FX CPU such as the Fugaku, which is under installation, and other commercial systems from Fujitsu and Cray.
•Visualization framework for large-scale data sets generated in the HPC environments.•Lua works as a glue for integrating the visualization pipeline functionality modules.•Hybrid MPI/OpenMP model is adopted to take advantage of the modern HPC architecture.
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3.
Equalizer 2.0-Convergence of a Parallel Rendering Framework Eilemann, Stefan; Steiner, David; Pajarola, Renato
IEEE transactions on visualization and computer graphics,
2020-Feb.-1, 2020-Feb, 2020-2-1, 20200201, Volume:
26, Issue:
2
Journal Article
Peer reviewed
Open access
Developing complex, real world graphics applications which leverage multiple GPUs and computers for interactive 3D rendering tasks is a complex task. It requires expertise in distributed systems and ...parallel rendering in addition to the application domain itself. We present a mature parallel rendering framework which provides a large set of features, algorithms and system integration for a wide range of real-world research and industry applications. Using the Equalizer parallel rendering framework, we show how a wide set of generic algorithms can be integrated in the framework to help application scalability and development in many different domains, highlighting how concrete applications benefit from the diverse aspects and use cases of Equalizer. We present novel parallel rendering algorithms, powerful abstractions for large visualization setups and virtual reality, as well as new experimental results for parallel rendering and data distribution.
We describe Chromium, a system for manipulating streams of graphics API commands on clusters of workstations. Chromium's stream filters can be arranged to create sort-first and sort-last parallel ...graphics architectures that, in many cases, support the same applications while using only commodity graphics accelerators. In addition, these stream filters can be extended programmatically, allowing the user to customize the stream transformations performed by nodes in a cluster. Because our stream processing mechanism is completely general, any cluster-parallel rendering algorithm can be either implemented on top of or embedded in Chromium. In this paper, we give examples of real-world applications that use Chromium to achieve good scalability on clusters of workstations, and describe other potential uses of this stream processing technology. By completely abstracting the underlying graphics architecture, network topology, and API command processing semantics, we allow a variety of applications to run in different environments.
Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can ...exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results.
The scene-rendering mechanism based on binocular vision is one of the key techniques for the VR globe to achieve immersion-type visualization of global 3D scenes. However, this special rendering ...mechanism also requires that the 3D scene is continuously drawn twice within one frame, which significantly affects the rendering efficiency of VR globes. Therefore, we propose a binocular parallel rendering method. This method first improves the current rendering process of VR globes by assigning the rendering tasks for the left and right camera of VR to be processed on different CPU cores, thereby achieving parallel rendering of binocular scenes. Second, due to the problem of inconsistent resolution of binocular scenes caused by different viewpoints for the left and right cameras, we propose a resolution synchronize algorithm. this algorithm conducts real-time synchronization on the resolution of scene in the rendering process and thus avoids the problem of erroneous binocular stereo matching. Finally, we validate the effectiveness of the method in this paper through experiments. The results of experiments indicate that while the method in this paper can ensure the consistency of binocular scene resolution, it can decrease the frame time of VR globes by approximately 27% on average.
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We present an efficient technique for out-of-core multi-resolution construction and high quality interactive visualization of massive point clouds. Our approach introduces a novel hierarchical level ...of detail (LOD) organization based on
multi-way kd-trees
, which simplifies memory management and allows control over the LOD-tree height. The LOD tree, constructed bottom up using a fast high-quality point simplification method, is fully balanced and contains all uniformly sized nodes. To this end, we introduce and analyze three efficient point simplification approaches that yield a desired number of high-quality output points. For constant rendering performance, we propose an efficient rendering-on-a-budget method with asynchronous data loading, which delivers fully continuous high quality rendering through LOD geo-morphing and deferred blending. Our algorithm is incorporated in a full end-to-end rendering system, which supports both local rendering and cluster-parallel distributed rendering. The method is evaluated on complex models made of hundreds of millions of point samples.
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Large high-resolution displays (LHRD) enable visualization of extremely large-scale data sets with high resolution, large physical size, scalable rendering performance, advanced interaction methods, ...and collaboration. Despite the advantages, applications for LHRD can be developed only by a select group of researchers and programmers, since its software implementation requires design and development paradigms different from typical desktop environments. It is critical for developers to understand and take advantage of appropriate software tools and methods for developing their LHRD applications. In this paper, we present a survey of the state-of-the-art software frameworks and applications for cluster-based LHRD, highlighting a three-aspect taxonomy. This survey can aid LHRD application and framework developers in choosing more suitable development techniques and software environments for new LHRD applications, and guide LHRD researchers to open needs in LHRD software frameworks.
With the increasing of computing ability, large-scale simulations have been generating massive amounts of data in aerodynamics. Sort-last parallel rendering is the most classical image compositing ...method for large-scale scientific visualization. However, in the stage of image compositing, the sort-last method may suffer from scalability problem on large-scale processors. Existing image compositing algorithms tend to perform well in certain situations. For instance, Direct Send is well on small and medium scale; Radix-k gets well performance only when the
k
-value is appropriate and so on. In this paper, we propose a novel method named mSwap for scientific visualization in aerodynamics, which uses the best scale of processors to make sure its performance at the best. mSwap groups the processors that we can use with a (
m
,
k
) table, which records the best combination of
m
(the number of processors in subgroup of each group) and
k
(the number of processors in each group). Then in each group, using a m-ary tree to composite the image for reducing the communication of processors. Finally, the image is composited between different groups to generate the final image. The performance and scalability of our mSwap method is demonstrated through experiments with thousands of processors.
Rendering textures in real-time environments is a key task in computer graphics. This paper presents a new parallel patch-based method which allows repeatable sampling without cache, and does not ...create visual repetitions. Interchangeable patches of arbitrary shape are prepared in a preprocessing step, such that patches may lie over the boundary of other patches in a repeating tile. This compresses the example texture into an infinite texture map with small memory requirements, suitable for GPU and ray-tracing applications. The quality of textures rendered with this method can be tuned in the offline preprocessing step, and they can then be rendered in times comparable to Wang tiles. Experimental results demonstrate combined benefits in speed, memory requirements, and quality of randomisation when compared to previous methods.
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