發(fā)布時(shí)間：2018-03-22 11:09

  本文選題：太陽(yáng)　切入點(diǎn)：射電輻射　出處：《天文學(xué)報(bào)》2017年02期 　論文類型：期刊論文

【摘要】：天文軟件開發(fā)中迫切需要在單機(jī)環(huán)境下進(jìn)行高性能數(shù)據(jù)處理工作,但由于機(jī)器配置不同,采用傳統(tǒng)的多線程、CUDA(Compute Unified Device Architecture)+GPU(Graphic Processing Unit)等方式都存在明顯的局限,不利于天文軟件的快速移植和無(wú)縫運(yùn)行.對(duì)明安圖頻譜射電日像儀(MingantU SpEctral Radioheliograph,MUSER)數(shù)據(jù)處理系統(tǒng)開發(fā)中所采用的OpenCL(Open Computing Language)技術(shù)進(jìn)行介紹,并基于OpenCL實(shí)現(xiàn)H銉gbom CLEAN算法.整體工作通過(guò)Python語(yǔ)言和PyOpenCL擴(kuò)展包實(shí)現(xiàn)并行潔化處理.實(shí)驗(yàn)結(jié)果表明:基于OpenCL實(shí)現(xiàn)的CLEAN算法與基于CUDA實(shí)現(xiàn)的CLEAN算法具有大致相當(dāng)?shù)倪\(yùn)行效率,同時(shí)也可以無(wú)需修改代碼直接實(shí)現(xiàn)純CPU(Central Processing Unit)環(huán)境下的高性能數(shù)據(jù)處理,解決了對(duì)CUDA+GPU環(huán)境依賴的問題,在保證MUSER數(shù)據(jù)處理系統(tǒng)潔化過(guò)程性能的基礎(chǔ)上,提高了系統(tǒng)對(duì)硬件平臺(tái)的適用性.該工作驗(yàn)證了OpenCL在科學(xué)數(shù)據(jù)處理中的可用性,可以預(yù)見:由于OpenCL所具有的異構(gòu)環(huán)境下高性能計(jì)算特性,OpenCL將是未來(lái)天文高性能軟件開發(fā)的首選技術(shù).
[Abstract]:In the development of astronomical software, there is an urgent need for high performance data processing in a single computer environment. However, due to the different configuration of the machine, there are obvious limitations in the traditional methods of GPU(Graphic Processing unit, such as CUDAT computer Unified Device Architecture). This paper introduces the OpenCL(Open Computing language technology used in the development of MingantU SpEctral Radioheliographer data processing system, which is not conducive to the rapid transplantation and seamless operation of astronomical software. The algorithm of H gbom CLEAN is implemented based on OpenCL. The parallel and clean processing is realized by Python language and PyOpenCL extension packet. The experimental results show that the CLEAN algorithm based on OpenCL and CLEAN algorithm based on CUDA have approximately equal running efficiency. At the same time, the high performance data processing in pure CPU(Central Processing unit environment can be realized directly without modifying code. The problem of dependence on CUDA GPU environment is solved, and on the basis of ensuring the clean process performance of MUSER data processing system, It improves the applicability of the system to hardware platform. This work verifies the usability of OpenCL in scientific data processing. It can be predicted that OpenCL will be the first choice technology of astronomical high performance software development in the future because of its high performance computing characteristics in heterogeneous environment.
【作者單位】： 昆明理工大學(xué)云南省計(jì)算機(jī)技術(shù)應(yīng)用重點(diǎn)實(shí)驗(yàn)室;中國(guó)科學(xué)院云南天文臺(tái);云南省信息技術(shù)發(fā)展中心;
【基金】：中國(guó)科學(xué)院-國(guó)家自然科學(xué)基金委員會(huì)天文聯(lián)合基金項(xiàng)目(U1231205、U1531132)資助
【分類號(hào)】：P161

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