Research On Large Scale Three-dimensional Scene Rendering Method Based On C/G Architecture

Three-dimensional visualization is an important means in geo-science research,and three-dimensional simulation provides a more real sense of the user’s experiencefor three-dimensional visualization, but how to use and manage large amounts of dataeffectively is the fund a mental problem for a three-dimensional simulation of massscenes. With the rapid development of information technology, the fast progress ofhigh-performance CPU and multi-type GPU provides a strong hardware support forthe development of real-time three-dimensional simulation.Making comprehensiveuse of the advantages for CPU data management and GPU data rendering plays a veryimportant role in the efficiency promotion of three-dimensional simulation.This article focuses on the current situation of three-dimensional real-timesimulation study on the performance of your computer at home and abroad, and afurther study on how to effectively manage the CPU and GPU inside the computer tolower requirements for the performance of your computer.Also,considering thecurrent GPU feature of diverse types, this paper makes a research and puts forward apervasive sense of architecture from the application of universal perspective. Thesystem identifies the function of CPU and GPU and separates the close correlationbetween CPU and GPU to make the CPU and the GPU features more specific andexplicit.The main innovations made in this article as follows:(1). Presents C/G(CPU/GPU) a three-dimensional simulation method forasynchronous heterogeneous parallel system.This fully takes traditional methods into account to manage the utilization ofCPU/GPU which is lack of effective means, and it’s hard to effectively complete thebottle-neck problems in the synchronization of heterogeneous parallel system ofcoordination of the many types of GPU and CPU.By creating a data center monitoringand managing the use of CPU and GPU,separating CPU and GPU, reducing the degree of coupling between them, it provides an effective solution to the coordinationof various types of GPU and CPU.(2). Presents the effective three-dimensional rendering optimization algorithmbased on ant colony algorithm.(ACAUS,ant colony algorithm under the survival).This feedbacks consumption and efficiency of regional memory and informs thedeath of GPU particle ants, which improves GPU utilization rate by ant creating asemaphore. GPU uses polling mechanism to query its demise, increasing theindependence of ants, decreasing the system to monitor its consumption and furtherimproving the utilization of GPU.(3). Presents a one-way communication mechanism for optimizing the efficiencyof large-scale three-dimensional rendering of the scene.This manages and controls the work of CPU and GPU through the messages inthe data center management module, eliminating the traditional way between the CPUand GPU of waiting for each other, reducing the amount of communication betweenthe CPU and GPU, and completely changed the traditional full-duplex communicationway and optimizedthe communication mechanism for CPU and GPU.Based on the above innovative research, the main results achieved in this articleinclude:(1).For large-scale geo-science characteristics of three-dimensional sceneoptimized GPU memory data management.(2).For large-scale three-dimensional scene, analyzed and discussed on affectingthe efficiency of data, there are three main types of data:Long survival time, large amounts of data, low frequency of use (LBLD);Long survival time, larger amounts of data, high frequency of use (LCHD);Short survival time, extremely large amounts of data, high frequency of use(SSHD);From the perspective of its own characteristics of three data types, this paperdetailed discusses and makes research on three kinds of data in rendering approachand on the characteristics of various GPU memory，also formulates relevant systemsolutions for a large-scale three-dimensional scene simulation of the three data typesand theoretical basis and practical guidance for the future three-dimensionalsimulation.(3).Based on the characteristics of SSHD data, this paper also presents theoptimization method of data management. By analyzing the characteristics of SSHD data, it brings ant colony algorithm indata management and puts forward the ant colony algorithm for survival andmanagement, meanwhile, enhances the management for massive data and theefficiency of memory usage.(4).Improves the traditional CPU and GPU data communication method.It analyses the operating mode of traditional means of communication, anddiscusses the bottlenecks affecting the efficiency in the traditional way of working,then, presents how to overcome the bottlenecks that two sides cannot be effectivelyused from communication congestion and traffic information, after that, changes thetraditional two-way communication into the one-way.(5).Initially establishes the framework of asynchronous concurrent systems basedon C/G(CPU-GPU).From the standpoint of the demands for large scale three-dimensional scenesimulation, analyses the shortages of heterogeneous parallel systems, makesresearches on C/G technicaland functional architecture.The C/G system architecturepreliminary studied and established lays detailed research on the schema managementinvolved in C/G architecture; evaluation of the priority tasks; GPU memory allocationand management, the dynamic monitoring of CPU-GPU use, the coordination andmanagement in the data center with CPU-GPU, and so on.(6).Analyses and evaluates the C/G system in details.It analyses and evaluates the C/G system in details from the frame rate, theacceleration ratio of software, parallelization of memory hierarchy, computingintensity by using actual three-dimensional geo-science data.Finally, the theory is used to display3D seismic data, which improves thedisplay speed effectively and is helpful to high efficiency seismic interpretation.