本文選題：多體模擬 + 異構(gòu)平臺(tái)�。� 參考：《國(guó)防科學(xué)技術(shù)大學(xué)》2012年碩士論文

【摘要】：多體問(wèn)題，又稱(chēng)N-body問(wèn)題，研究多個(gè)質(zhì)點(diǎn)相互作用的運(yùn)動(dòng)規(guī)律，是力學(xué)和天體物理學(xué)的基本問(wèn)題之一，具有廣泛的應(yīng)用范圍，既能用于研究天體物理學(xué)中宇宙天體的演化和運(yùn)動(dòng)，又能用于研究分子動(dòng)力學(xué)中分子的運(yùn)動(dòng)規(guī)律和變化情況。多體模擬的計(jì)算復(fù)雜度較大，如果直接計(jì)算多體的兩兩之間的受力情況，計(jì)算復(fù)雜度達(dá)到O(N2)，即使使用改進(jìn)的算法，計(jì)算復(fù)雜度也達(dá)到O(NlogN)，隨著運(yùn)算規(guī)模的爆炸性增長(zhǎng)，傳統(tǒng)PC機(jī)的計(jì)算能力遠(yuǎn)遠(yuǎn)無(wú)法滿足N-Body問(wèn)題的求解需要，因此需要大型并行計(jì)算機(jī)來(lái)解決該類(lèi)問(wèn)題。目前巨型機(jī)中大多采用的是CPU-GPU異構(gòu)體系結(jié)構(gòu)，在異構(gòu)體系結(jié)構(gòu)中，CPU主要負(fù)責(zé)控制GPU以及對(duì)數(shù)據(jù)的采集和結(jié)果的收集，GPU負(fù)責(zé)計(jì)算，CPU在GPU進(jìn)行計(jì)算時(shí)處于空閑狀態(tài)，這對(duì)CPU資源造成了極大的浪費(fèi)。 本文在CPU-GPU異構(gòu)平臺(tái)上，面向多體問(wèn)題在計(jì)算機(jī)中的模擬過(guò)程，對(duì)天體物理學(xué)和分子動(dòng)力學(xué)應(yīng)用分別進(jìn)行GPU加速，并基于CPU-GPU異構(gòu)體系結(jié)構(gòu)對(duì)多體模擬提出一種CPU和GPU協(xié)同運(yùn)算的兩級(jí)并行策略，充分利用異構(gòu)系統(tǒng)的計(jì)算資源；為確保計(jì)算性能最佳，，本文總結(jié)了使用GPU進(jìn)行計(jì)算的MPI進(jìn)程最佳數(shù)目和最佳位置的公式；本文提出了根據(jù)CPU和GPU的運(yùn)算性能差異提出動(dòng)態(tài)更新任務(wù)分配比例的算法，保證CPU和GPU之間的計(jì)算負(fù)載平衡。以上工作為今后對(duì)多體問(wèn)題和異構(gòu)體系結(jié)構(gòu)的研究工作奠定了堅(jiān)實(shí)的基礎(chǔ)。
[Abstract]:Multi-body problem, also called N-body problem, is one of the basic problems in mechanics and astrophysics, which can be used to study the evolution and motion of astrophysics. It can also be used to study the movement and changes of molecules in molecular dynamics. The computational complexity of multibody simulation is very high. If we directly calculate the force between the two parts, the computational complexity can reach ON2G, even if the improved algorithm is used, the computational complexity will reach ONlogNnn, which increases with the explosive increase of the operation scale. The computing power of traditional PC is far from satisfying the need of solving N-Body problem, so it needs a large parallel computer to solve this kind of problem. At present, most of the supercomputers use CPU-GPU heterogeneous architecture. In the heterogeneous architecture, the CPU is mainly responsible for controlling GPU and collecting data and results. The CPU is responsible for calculating the idle state of GPU. This is a great waste of CPU resources. In this paper, on the CPU-GPU heterogeneous platform, the simulation process of multi-body problem in computer is simulated, and the applications of astrophysics and molecular dynamics are accelerated by GPU, respectively. Based on the CPU-GPU heterogeneous architecture, a two-level parallel strategy of CPU and GPU cooperative operation is proposed to make full use of the computing resources of heterogeneous systems, in order to ensure the best computing performance. This paper summarizes the formula of the optimal number and location of MPI processes calculated by GPU, and proposes an algorithm to dynamically update the task allocation ratio according to the difference in the performance of CPU and GPU, so as to ensure the computational load balance between CPU and GPU. The above work lays a solid foundation for the future research on multi-body problem and heterogeneous architecture.
【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：TP338.6

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