發(fā)布時(shí)間：2018-01-09 15:32

  本文關(guān)鍵詞：二維磁場(chǎng)重聯(lián)的OpenCL研究　出處：《中國(guó)地質(zhì)大學(xué)（北京）》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： CESE時(shí)空守恒算法 并行 GPU OpenCL架構(gòu) MPI

【摘要】：太陽大氣層的爆炸，最大的破壞源自日冕物質(zhì)拋射，他們高速射離太陽外層大氣，并將爆炸產(chǎn)生的巨量等離子體向地球碰撞的軌道中射入，這就是太陽耀斑爆發(fā)。耀斑爆發(fā)的主要原因是太陽磁場(chǎng)中磁力線的重新排布，即磁重聯(lián)。 本課題是以均勻網(wǎng)格下二維磁場(chǎng)重聯(lián)為依據(jù)，運(yùn)用磁流體力學(xué)（MHD）數(shù)值模擬對(duì)磁場(chǎng)重聯(lián)、太陽風(fēng)暴等一系列等離子體物理現(xiàn)象和運(yùn)動(dòng)過程進(jìn)行研究，使用近幾年發(fā)展的高效率、高分辨率、高精度的新型數(shù)據(jù)格式時(shí)間空間守恒（CESE）格式，又稱時(shí)空守恒（CESE）方法進(jìn)行數(shù)值求解。隨著物理研究過程的日益復(fù)雜，空間分辨率的不斷提高，數(shù)據(jù)規(guī)模的不斷加大，計(jì)算量大、速度慢的問題日益顯著，運(yùn)用傳統(tǒng)的串行CESE方法已經(jīng)（遇到了無法避免的性能瓶頸）很難滿足研究者的實(shí)時(shí)需求，如何高效加速數(shù)據(jù)運(yùn)算成為一個(gè)非常值得關(guān)注的問題。 通用GPU的出現(xiàn)，使得一些計(jì)算密度高、邏輯結(jié)構(gòu)簡(jiǎn)單的大規(guī)模數(shù)據(jù)并行運(yùn)算得到了一種新的解決方案。GPU的發(fā)展不僅是在圖形渲染、圖像處理等方面，在通用計(jì)算特別是浮點(diǎn)并行運(yùn)算方面已取得很大的突破和成功，它能在有限的面積上實(shí)現(xiàn)很強(qiáng)的處理能力和很高的存儲(chǔ)器帶寬。隨著Shader Mode、CUDA、OpenCL等架構(gòu)體系和相應(yīng)平臺(tái)技術(shù)的發(fā)展運(yùn)用，GPU在性能上更是有了進(jìn)一步的提升，同時(shí)發(fā)展速度也遠(yuǎn)遠(yuǎn)高于CPU，基本上每年都會(huì)產(chǎn)生新一代的GPU。 OpenCL（Open Computing Languange，開放式計(jì)算機(jī)語言），是一種異構(gòu)資源解決方案，它提供了一個(gè)高效的、相互開發(fā)的、可自由移植的平臺(tái)。本文的主要研究?jī)?nèi)容是利用GPU的強(qiáng)大數(shù)據(jù)并行計(jì)算能力，使用OpenCL架構(gòu)和MPI消息傳遞模型，將CESE核心算法重構(gòu)優(yōu)化，提出一種多線程的基于OpenCL的并行CESE算法，使之與GPU體系完好結(jié)合，得到更好的加速比。利用OpenCL的實(shí)現(xiàn)步驟如下：研究CESE數(shù)值模型和主體計(jì)算步驟，分析耗時(shí)的關(guān)鍵程序；使用MPI和OpenCL并行編程模型，編寫為GPU和CPU的高效混合并行計(jì)算；研究進(jìn)程間，主機(jī)和設(shè)備的通信問題，進(jìn)行調(diào)優(yōu)測(cè)試。經(jīng)試驗(yàn)得出，使用OpenCL的并行CESE算法，比傳統(tǒng)串行算法提速了5倍左右。文章還對(duì)并行解決方案的優(yōu)勢(shì)和不足進(jìn)行了分析，從而加深了對(duì)GPU體系架構(gòu)和計(jì)算模型的理解。
[Abstract]:The biggest damage to the sun's atmosphere comes from coronal mass ejections, which shoot at high speed from the sun's outer atmosphere and fire huge amounts of plasma from the explosion into the orbit of the Earth's collision. This is the solar flare burst, the main reason for the flare burst is the rearrangement of the magnetic field in the solar magnetic field, that is, magnetic reconnection. Based on the two-dimensional magnetic reconnection under uniform grid, a series of plasma physical phenomena and motion processes, such as magnetic field reconnection and solar storm, are studied by MHD numerical simulation. Use the new data format of high efficiency, high resolution and high precision developed in recent years. With the increasing complexity of the physical research process, the spatial resolution continues to improve, the scale of the data continues to increase, and the amount of calculation is large. The problem of slow speed is becoming more and more obvious, and it is difficult to meet the real-time requirements of researchers by using the traditional serial CESE method (encountered an unavoidable performance bottleneck). How to speed up data operation efficiently becomes a very important problem. With the emergence of general GPU, some large scale data parallel operations with high computing density and simple logic structure have been developed not only in graphics rendering, but also in graphics rendering. In the field of image processing, great breakthrough and success have been made in general computing, especially in floating-point parallel computing. It can achieve very strong processing power and high memory bandwidth in a limited area. OpenCL and other architecture systems and the development of the corresponding platform technology has been further improved in performance, at the same time, the speed of development is far higher than CPU. Basically, a new generation of GPUs is produced every year. OpenCL(Open Computing language, an open computer language, is a heterogeneous resource solution that provides an efficient solution. The main research content of this paper is to utilize the powerful data parallel computing ability of GPU, using OpenCL architecture and MPI message passing model. This paper proposes a multi-thread parallel CESE algorithm based on OpenCL to optimize the reconstruction of the CESE core algorithm, which is integrated with the GPU system. The implementation steps of using OpenCL are as follows: the numerical model of CESE and the main calculation steps are studied, and the key procedures of time consuming are analyzed. Using the parallel programming model of MPI and OpenCL, the high efficient hybrid parallel computing for GPU and CPU is written. The communication between process, host and equipment is studied, and the tuning test is carried out. The parallel CESE algorithm using OpenCL is obtained by experiment. The paper also analyzes the advantages and disadvantages of parallel solutions, thus deepening the understanding of GPU architecture and computing model.
【學(xué)位授予單位】：中國(guó)地質(zhì)大學(xué)（北京）
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P182.5;TP338.6

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