本文選題：多核GPU + 并行運(yùn)算��； 參考：《杭州電子科技大學(xué)》2015年碩士論文

【摘要】：作為衡量一個虛擬裝配系統(tǒng)優(yōu)越與否的重要標(biāo)準(zhǔn)，碰撞檢測問題受到人們的廣泛關(guān)注。當(dāng)前，實(shí)時性和精確性是判斷碰撞檢測算法的關(guān)鍵標(biāo)準(zhǔn)，因此如何利用日漸成熟的計算機(jī)硬件的并行架構(gòu)，來實(shí)現(xiàn)復(fù)雜場景下的精確的實(shí)時碰撞檢測成為人們當(dāng)前的研究重點(diǎn)。 在復(fù)雜場景中，連續(xù)碰撞檢測（Continuous Collision Detection，CCD）依然很難做到實(shí)時效果。隨著CPU并行架構(gòu)的實(shí)現(xiàn)，本文提出了一種CPU多核加速的碰撞檢測算法來提高虛擬裝配系統(tǒng)性能。通過利用硬件的多核性能，提出了一個空間分解理論，然后利用動態(tài)任務(wù)分配策略把碰撞檢測任務(wù)均衡的分配到所有內(nèi)核上，使每個內(nèi)核上的的任務(wù)負(fù)載均衡。最后通過數(shù)據(jù)分析，該算法可以有效提高碰撞檢測效率。 相較于具有較強(qiáng)邏輯計算能力CPU來說，具有強(qiáng)大浮點(diǎn)計算能力的GPU在有龐大運(yùn)算量的裝配系統(tǒng)中更有優(yōu)勢。由于人們在進(jìn)行數(shù)學(xué)建模時不可避免出現(xiàn)誤差，從而導(dǎo)致本不應(yīng)該有碰撞接觸的零部件出現(xiàn)重疊或者嵌套現(xiàn)象。 針對以上問題，，我們利用現(xiàn)代GPU強(qiáng)大的高密度計算能力及其多核的性能，提出了一種實(shí)時的GPU加速的并行碰撞檢測算法。主要工作內(nèi)容如下： （1）提出了一個新的基于GPU加速的并行碰撞處理框架，利用連續(xù)碰撞檢測保證物體在移動過程中沒有碰撞遺漏現(xiàn)象。 （2）為了解決CPU與GPU之間由于帶寬限制所造成的數(shù)據(jù)吞吐量較小而引起的通信瓶頸問題，改進(jìn)了基于碰撞流優(yōu)化的CCD方法，以改善碰撞檢測的整體性能，實(shí)現(xiàn)系統(tǒng)的實(shí)時效果。 （3）將離散碰撞檢測（Discrete Collision Detection，DCD）與連續(xù)碰撞檢測結(jié)合。把三角行碰撞檢測（Triangle Intersection Detection，TID）結(jié)合到當(dāng)前的基于CCD的多核碰撞檢測算法中，利用混合的碰撞檢測來避免由于建模誤差的緣故導(dǎo)致在初始化時彼此間有嵌套、重疊現(xiàn)象而無法移動部件的問題。
[Abstract]:As an important criterion to measure the superiority of a virtual assembly system, collision detection has been paid more and more attention. At present, real-time and accuracy are the key criteria for judging collision detection algorithms. Therefore, how to use the increasingly mature parallel architecture of computer hardware to achieve accurate real-time collision detection in complex scenes has become the focus of current research. In complex scenarios, continuous Collision detection is still difficult to achieve real-time effects. With the implementation of CPU parallel architecture, a CPU multi-core accelerated collision detection algorithm is proposed to improve the performance of virtual assembly system. By using the multi-core performance of hardware, a spatial decomposition theory is proposed, and then the collision detection task is evenly distributed to all kernels using dynamic task allocation strategy, which makes the task load balance on each kernel. Finally, through data analysis, the algorithm can effectively improve the efficiency of collision detection. Compared with CPU with strong logical computing power, GPU with strong floating-point computing capability has more advantages in assembly systems with large computational complexity. Due to the inevitable errors in mathematical modeling, there is overlap or nesting of parts which should not have collision contact. To solve the above problems, we propose a real-time parallel collision detection algorithm based on GPU acceleration using the powerful high density computing power of modern GPU and its multi-core performance. The main tasks are as follows: A new parallel collision processing framework based on GPU acceleration is proposed. Continuous collision detection is used to ensure that there is no collision omission in the moving process. In order to solve the communication bottleneck problem between CPU and GPU caused by the low data throughput caused by bandwidth limitation, the CCD method based on collision flow optimization is improved to improve the overall performance of collision detection and realize the real-time effect of the system. The discrete Collision Detection (DCD) is combined with continuous collision detection. In this paper, Triangle Intersection Detection (TID) is combined with the current multi-core collision detection algorithm based on CCD, and the hybrid collision detection is used to avoid nesting each other during initialization due to modeling errors. The problem of overlapping and immovable parts.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TG95;TP391.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 趙罡;王超;侯文君;金鉞;;復(fù)雜產(chǎn)品虛擬裝配系統(tǒng)的人機(jī)交互技術(shù)[J];北京航空航天大學(xué)學(xué)報;2009年02期

2 蔣建春;汪同慶;;異構(gòu)多核處理器的任務(wù)調(diào)度算法[J];計算機(jī)工程與應(yīng)用;2009年33期

3 侯偉偉;寧汝新;劉檢華;;虛擬裝配中基于精確模型的碰撞檢測算法[J];計算機(jī)輔助設(shè)計與圖形學(xué)學(xué)報;2010年05期

4 杜鵬;唐敏;童若鋒;;多核加速的并行碰撞檢測[J];計算機(jī)輔助設(shè)計與圖形學(xué)學(xué)報;2011年05期

5 唐敏;MANOCHA Dinesh;童若鋒;;基于SIMD指令的柔性物體并行碰撞檢測[J];計算機(jī)學(xué)報;2009年10期

6 沈佳中;王毅剛;;力反饋技術(shù)在虛擬裝配中的應(yīng)用研究[J];杭州電子科技大學(xué)學(xué)報;2013年05期

7 劉榮;趙文元;;蟻視:做中國的虛擬現(xiàn)實(shí)產(chǎn)品[J];科技創(chuàng)新與品牌;2014年09期

8 張忠祥;王士同;;三角形對的快速相交測試[J];計算機(jī)工程與設(shè)計;2010年04期

9 翁壽松;關(guān)于摩爾定律的爭論[J];微電子技術(shù);1998年06期

10 劉檢華,姚s

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