serial adj. 1. 連續(xù)的;一連串的;一系列的。 2.按期出版的;(小說(shuō)等)連載的;連續(xù)刊行的;連續(xù)廣播的。 3.分期償付的。 4.【計(jì)算機(jī)】中行的;串聯(lián)的。 a serial number 1. 序號(hào);編號(hào)。 2. 【軍事】軍號(hào);入伍編號(hào)。 a serial publication 陸續(xù)出版的成套出版物。 a serial story 連載小說(shuō)。 serial rights 連續(xù)刊載的版權(quán)。 n. 1.連載小說(shuō);連續(xù)廣播;連續(xù)電視;連本影片。 2.定期刊物。 3.【軍事】行軍梯隊(duì)。 in serial order 順次。 write in serials 寫(xiě)連載小說(shuō)(等)。
Firstly , to improve the mpiformatdb ’ s speed , a novel parallel algorithm based on shared memory architecture is presented . by adding openmp directives , the cycled parallel structure is formed from the serial algorithm 為了提高mpiformatdb的性能,本文提出一種基于共享存儲(chǔ)結(jié)構(gòu)的并行算法,通過(guò)在原串行算法中增加openmp編譯指導(dǎo)命令來(lái)構(gòu)造循環(huán)級(jí)并行結(jié)構(gòu)。
Through analyze the virtues and disadvantages of the serial algorithms and parallel algorithms of association rules mining , then we experiment with experiment data to evaluate the performance of the parallel algorithms based on apriori algorithm in pvm environment 通過(guò)深入分析挖掘關(guān)聯(lián)規(guī)則的串行算法和并行算法的優(yōu)缺點(diǎn),并且在pvm環(huán)境下對(duì)基于apriori算法的并行算法進(jìn)行了實(shí)現(xiàn)。
The traditional serial algorithm ca n ' t do work well for the data ocean quickly and correctly , it also important to research the parallel algorithm . this paper analysis the main parallel algorithm and models , and find there are two problema : how to use the capability of the processors and the information number of the transmission between the processors . this paper extend the twma to ptwm , and ptwma solve the problem by the method of table corresponding , and the idea that the algorithm need not to transmit the large item sets 本文通過(guò)分析當(dāng)前主要的并行模型、算法,總結(jié)出它們面臨的共同問(wèn)題是:處理機(jī)容量的限制和處理機(jī)需要傳輸大量的數(shù)據(jù),于是,本文在twma的基礎(chǔ)上提出了ptwma ,采用了表對(duì)應(yīng)技術(shù)、以及算法本身不需要反復(fù)傳輸大項(xiàng)集的策略來(lái)克服了上述兩個(gè)問(wèn)題。
Serial algorithm improves decoding performance greatly ; serial algorithm finds the better trade - off between performance and complexity , it is a good decoding algorithm with high application value . ( 5 ) introduce the background of quantized decoding and basic theory . analyse effect of quantized decoding , research the impact of limited quantized to serial decoding , and present feasible project for quantized decoding ( 5 )介紹了量化譯碼的背景和量化原理,分析了量化譯碼對(duì)譯碼器實(shí)現(xiàn)的重要作用,基于串行譯碼算法,以消息種類的不同分別研究了有限長(zhǎng)量化對(duì)譯碼性能的影響,并提出可行的串行量化譯碼方案,其性能接近連續(xù)譯碼性能。
( 3 ) combined with probability statistic knowledge , introduce the basic theory of message passing algorithm ; analyse the classical decoding algorithm of ldpc codes , including sum product algorithm which based on probability and llr , and min sum algorithm . ( 4 ) research message passing process on the tree ; according spa , turn the flooding schedule to serial schedule based on c - nodes and v - nodes , namely serial algorithm and , analyse de and complexity ; simulations show that the both serial algorithms could improve decoding performance , improve convergence property , reduce complexity ( 4 )研究了和積譯碼算法在樹(shù)上的消息傳遞過(guò)程;在ldpc碼經(jīng)典譯碼算法基礎(chǔ)上,將洪水消息傳遞機(jī)制轉(zhuǎn)換成基于校驗(yàn)節(jié)點(diǎn)的串行消息傳遞機(jī)制和基于變量節(jié)點(diǎn)的消息傳遞機(jī)制,分別對(duì)應(yīng)串行譯碼算法和串行譯碼算法,并對(duì)密度進(jìn)化和譯碼復(fù)雜度等方面進(jìn)行分析;仿真結(jié)果表明,兩種串行譯碼算法都使譯碼性能得到明顯提高,改善了消息收斂特性,降低了譯碼復(fù)雜度。
The algorithm of upgrading of general face recognition system is based on all serial algorithm in a single computer , it is very slow to deal with a large amount of data , and the efficiency is low . so , this article introduces the application of grid computing in face recognition system , upgrades the original serial algorithm of face data into parallel algorithm in the grid platform by using mpi parallel program , realizes the already existing updated algorithm of the recognition of face to be processed in the distributed computers , which has strengthened the systematic ability to deal with a large amount of data , in order to improve systematic performance 常規(guī)人臉識(shí)別系統(tǒng)中的更新算法都是基于單機(jī)的串行算法,在處理大量數(shù)據(jù)的時(shí)候速度慢,效率低,介紹了網(wǎng)格計(jì)算在人臉識(shí)別系統(tǒng)中的應(yīng)用,把原來(lái)的人臉數(shù)據(jù)更新串行算法改為并行算法并通過(guò)編寫(xiě)mpi并行程序移植到該網(wǎng)格計(jì)算平臺(tái)中運(yùn)行,實(shí)現(xiàn)了原有人臉識(shí)別系統(tǒng)中更新算法的分布式處理,增強(qiáng)了系統(tǒng)處理大量數(shù)據(jù)的能力,以達(dá)到提高系統(tǒng)性能的目的。