Research On Key Techniques Of Heterogeneous Parallel Computing For Virtual Reality Simulation Platform

The traditional single-threaded algorithm for single-core processor is difficult tomeet the real-time requirements of mass data processing; it also cannot give full playto the potential of multi-core processors computing. Parallel computing technique hasbecome the forefront of computer performance optimization techniques. Especially inthe areas of multimedia and three-dimensional graphics in which a high demand forreal-time is required, demand for rapid processing of massive data is particularlyurgent. This dissertation is oriented to VRGIS, a virtual reality simulation platformintegrated geographic information system. The software has a carrying capacity forthree-dimensional metro-level model data and three-dimensional terrain data. VRGISalso supports a variety of complex natural phenomena simulation and visualizationeffects, and has a high picture fidelity and real-time interaction. In this dissertation,various parallel computing techniques are studied to solve a variety of performancebottlenecks of VRGIS from skeletal animation to particle systems inthree-dimensional simulation.The major research work includes the following five aspects:1. To establish an performance evaluation model of parallel computing bycomparison among multiple peer technique solutionsIn this dissertation, with the theoretical basis of Amdahl’s law an assessmentmechanism by multiple parallel computing technique solutions is introduced toimprove the performance evaluation model for parallel computing. Among the fivesets of parallel computing technique programs in this dissertation, the latest one isOpen Computing Language (OpenCL) which can be used for both central processingunits (CPUs) and graphics processing units (GPUs). Besides CPU and GPU have theirown dedicated parallel computing technique. Open Multi-Processing (OpenMP) andStreaming SIMD Extensions (SSE) are oriented to CPU, while OpenGL ShadingLanguage (GLSL) and Compute Unified Device Architecture (CUDA) are oriented toGPU.2. To design multiple parallel computing schemes for the matrix palettealgorithm of skeletal animationExisting parallel computing schemes SSE and GLSL are implemented andimproved for skeletal animation. With new techniques such as CUDA and OpenCL new parallel computing schemes are produced for skeletal animation, comparison andanalysis are performed among these parallel computing schemes with differenttechniques. Based on the former multiple schemes, we design a strategy to auto-selectthe best parallel scheme for skeletal animation.3. To design a parallel computing scheme based on OpenCL for fountainsimulation with Berlin noise wind disturbance by particle systemIn order to improve the fidelity of the simulation results random disturbancefactor such as Berlin noise is involved. A parallel computing scheme based onOpenCL is used to perfect the performance of particle system running on both CPUand GPU.4. To construct a principle to map multiple parallel tasks to multiple paralleldevicesWhile multiple tasks are running at the same time with the purpose to fullyexploit the heterogeneous parallel computing capabilities of multiple devices such asCPU and GPU, two separated modules skeletal animation and particle system aretreated as a whole multi-task system. Then a principle to map multiple parallel tasksto multiple parallel devices is studied to get further performance optimization forsimulation platform of virtual reality.The innovation of this dissertation is mainly reflected in three aspects:1. To propose the matrix palette algorithm for skeletal animation based onOpenCL for heterogeneous platform mixed CPU and GPU. Function innovation:Portability is advanced for skeletal animation algorithm matrix palette from CUDA toOpenCL. Because original algorithm based on CUDA is dependent on particularNVIDIA GPU, while algorithm based on OpenCL for matrix palette is generallyapplicable to a variety of GPU. Performance innovation: With two set of referencebenchmark including serial algorithm and traditional parallel algorithm by SSE andOpenMP on CPU, OpenCL version of the matrix palette algorithm on CPU gets aspeedup of3.9and1.5.2. To design a strategy to auto-select the best parallel scheme for skeletalanimation. Function innovation: we design five sets of parallel computing schemes forskeletal animation. The latest scheme is based on OpenCL which can be used for bothCPUs and GPUs. Besides CPU and GPU have their own dedicated parallel computingtechnique. OpenMP and SSE are oriented to CPU, while GLSL and CUDA areoriented to GPU. Performance innovation: on different GPUs and CPUs, auto-selectthe available and best parallel scheme for skeletal animation. 3. To design a parallel computing scheme based on OpenCL for fountainsimulation with Berlin noise wind disturbance by particle system for heterogeneousplatform mixed CPU and GPU. Performance innovation: With a reference benchmarkwhich is formed by serial algorithm on CPU, OpenCL gets speedup of3.4on CPUand65on GPU.Multiple parallel computing techniques are studied to accelerate the performanceof skeletal animation and particle system involved in virtual reality. Researchers anddevelopers can get valuable proofs and clues from this dissertation while thefollowing decisions are looking forward to be made: whether to parallelize the serialalgorithm, whether to port outdated parallel algorithm to the latest version, whether toupdate the parallel hardware device.