                      ˿µϣ20050313գ

05.03.12ûи
05.03.13, ձ100졷ϵбαĻ
05.03.13, ܿϵбٻ
05.03.13, һ̬ʵı걾硰ˮ˶
05.03.13, ˮȫһȷϡˮĿԴĹ̡
05.03.13, ˮΪʲôӦùȳɫGDP
05.03.13, ơҲ˵J.D.ѧʿ˶ʿǲʿѧλ
05.03.13, tianxinӡtianxinBerkeleyWolfxjstevenJ.D. ʲôѧλ
05.03.13, ¡ŷƴӸС
05.03.13, 廪ѧZhixin Ba, Haichang Zhou, Huai Zhang and Zhenxiao Yang 
IEEE
05.03.13, ¥˷Ļ

˿(www.xys.org)(xys.dxiong.com)(xys.3322.org)(xys.freedns.us)

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ձ100졷185 20050311

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˳׵ţ٣1990ǰټʱ߶Դ
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2003ǰٸΪһЩ߿ʼȫţ̺޹
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Աļ̡ٱλҵʿ˵е䷽Ǵר
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ˮӽгֵ⣬ʡԵ桢ϸ١ͼˮ
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ҪȺ쵼ˣ2002ϷԼ˹ۼһã̿ɳ
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ȻȻǸһеģǸ
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ڷˮϣ̬Ҳǵӵ˼¡Ϊ
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˵кģһڷˮ˶Ҳֵķǳԡ
ˮ˶һʮص󣬾ҡԣ
ˣִĴ棬ǾٰݽǩԶ
硢ǧ֮Ƨطˮ衣˷չйҵ档
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ֻ25%չйҪ޽°ӣڹˮȡͷ
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Ҫͣ̽衣һԷչйġʴίԱ
ˮίԱᱨۡ

ĿǰһЩطȷʵһЩ͹ûо֤Ͳִ
Դ˷Ѻ̬ƻ󡣴̬ѧĽǶȿ̬
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ݣ

練ˮ˶Ʋ

ǰһֽˮίԱᣨWCD֯һ
ˮӵĹ룬Ȼ࣬СǷˮӱ棬
ˮӴᣬָˮաһЩýΪҡźȷʵɱ
һЩˣǵķˮ˶Ʋ֮󣬻˲࣬Ϊ
ˮ粻ԴزӳΪΪ˳
巴ˮ۵бҪعһΧƷ뽨Ӷȫ̡

һ

ˮ˶ǴӰİ˹ӿʼġ

˹ˮӵĽ蹤̿ʼ1960꣬ʮʱ䣬1970꽨ɡ
ǰͳʿ˺չУ֯쵼˿Ӣ
ɫзְսڽϣҲûĿ
ѡΪ飬ǽӵʽǼΪ
ʱսʱڣκʶ̬ԭ򣬰˹ȻҲͳ
Ϊý幥Ŀꡣ֮ӽɺ70ǻ˳֮
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ʷ£˹ӳΪýеİӡ

ڶ԰˹ϣý岢ûԼġ͹ۡ
ԭȫʵǡֵطˮӵĹǷǣǲ˹һ㡢
ĹַͰ˹ΪҺĺô
ˮӵĸӰ죬ۡ



Ž뷴Ӷ漤ңΪ˴侲Ϳ͹۵
СȻ˵֯һʱ֯Դ
רŵĵо֯ˮίԱᣨWCD֯
1997꣬20001116շձ桶ˮ뷢չһµľ
߿ܡWCD棩ͬʱ塣

WCDֹ10ɣҪݰá̬ᡢ
ˮܵѡ񡢾(ƻ֯)෢չˮԴ߿ܡӦõ
ԼίԱ̡棨¼˵480ҳ

WCDĻǷӡչģһܵ㷺
ӵ80ԱίԱᣨICOLDڶĳԱWCD
еĴ˳ֵĽ¶СݹҪ¼㣺

һ	WCDԱĴԡרҵˮ׼ɡ

WCD12ԱֱӡȡĴǡɱ䡢
¹ϯǰϷǵĽ¶˹ΡԴˣɣ

112дķʿԱûһкˮ
ˣһǳӵ򡣡ױǣ ĳЩWCDίԱȷ
дͼǷԱʾɡίίԱᣩ

2WCDίԱĵֲǲģҲȱԣûж˹й
ҵĴôûȡˮίᣨWWCʹˮί
ԱᣨICID߹ˮЭᣨIHAʴίԱᣨICOLDҪ
֯ڸñ׼ڼ䲢û̳Э̣ո
֮ǰҲδʾίίԱᣩ

312ѡίԱĲһ壬һ12
졢ԸṩԱɵС顱һ¹ѯ
߻ύˮ÷дߵԿЩ˾Ƿߣ
ǶԿˮԴַʿӡԱΪ
硢̱ġ̲ڤʹǣ
ڴˣһ̬ίԱõƽġƫıǲܵġ
YOGENDRA PRASAD ҵ޹˾ϯִж£

	桱Ŀѧܵɡ

1еĴ٣ȱԡ

WCDѡȡ125ӽձ飬8ӽнϸĵ飬ȫ
45,000Уֻ0.3%ѡȡϸо
Էǳԡ ѡȡİҪĿ˹
˹工ˡô󣩡ʴίԱɱѡġ
۵8ӵĴԡֻһ̩Pak Mumӣǹȥ10ڽ
ģİ20-70֮ǰ滮ġʴίԱΪһԴ
ʵʵĹӦԵ̽УڿλݵĴ
ӣЩеĴԭϷWCDĽ顱ʴίԱᣩ
ĴӣTucurui, Balbina, SamuelCurua-UnaЩӲ
ĴӡǶѷAmazonֽѲٽӣ
صĻ⣬ǵĹӺͳڰͬصģ
ܴ

2	û֤ݵ¶ԡ

ñ桰ûͳƱ׼Щ򵥻оʵ
ӣóһЩĽۡһ棬ûм֧֣ƪǿ
Ӱã׵ó½ۣˮӽȫԵġ
ɵóӻϰƶʹĽۡ

ԡӸı˺Ļѧɷ֣Ĵŷ
ǳͳûκ֤ݡȻмûṩйصºѧɷָı
ص֤ݣҲûṩܲˮȼտȼ
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Ľ͡ίίԱᣩ

ЩٶûпѧۻͼʵķۣҲûôо
Լ˵ӶԹҷչʵȥ飬ˣӵĹ
״ͿǷǳƫġֻƾŸ˵ĸо
ʶϸĹˮӵϢд桱ӡȣ

3ûңìܡ

ָйĴӽռ๤27%
ְڳ󡢵·˿Ǩƣڱµ
44ᵽйڽռ34%
֮ʹìܣ7%й˿൱˵ġίί
ԱᣩڴӽĹۣ4,000
8,000ˣֵûɣ䷶Χ200%˹
Aswanӵ5ˣҾѵõɹİá

	ȨҵϢۡ

1۵Ƭ棬ƫ

ἰΪĴͨĵضӵЧ桱
ʴίԱᣩ˵ӡǣӶڻŸã
ôȴԡô󣩡ñ˺ܶˮĴ
ԽɸӰӡȻûǾ޴ģˮڹ
ڽ˺ͻҵȷľ޴ûڱеõ֡
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ˮίԱʱĳԲͬģƺûжԴӵ͹ע
Ȩͻ˹̹ĽۺͽûȨӽ
ף˲ܽΪȻĵ򡣡˹򣩡̫ǿ˴ӵ
ЧӦᵽĻ·˹ûôأû˷
ӶĹס·˹ĿȷĿ꣬ʵʩУ
κβ֧۵Ĳ϶֮߸WCDν֪ʶ⡱ķ
оԵľӣѼʵδ֤õļ衱ӡ


2Ȩҵ

ӡȹҵоһרСɵģЩд󲿷ӻ
ˮԴ̹ϵУWCDӡҲûύڶӡ
۵Ĺ۵֮ǰӡѯڴķʿ
йڡӣӡȾ顯Ĺ۵ƫģˡӡȹо
ߵķӹ۵㡣СӡȰо½жദõݲдԡ
WCDҲӡԳۣǣӡĹ۵㲢ûеõWCD
ĲɡNagarjunasagarBhakraӳӡˮЧӦĹ
̶û䱨еõǡáӡ

֮ܶƪĽûƽ͵ķʽͿѧĻ˼
סľǲģ󲿷ֻر˴еҪ
ãЩӽҵķչȷ淢Ҫá
 չĹؼӴչӵķչӦñƬ
赲ʿWCDõķõ֤֣䷽
ûоʵ֤õ֤ûаӽķչ̡
˽ӽͻĸơй

3Ϣۡ

磬Ѱİ˹ӵͣʵϣˮӵĽ貢
˵äĿ޽˹߰ӵĹ滮оʼ1820ֱ꣬2050
̲ŵʵʩˮġ̼ѡ/ԡӰ
ȷ涼˴ȫоΪ˸˹һ
ۣʴίԱ1993ڿٿ飬רۻ϶԰˹
̵ᡢԼӰȷȫۺǸù
ȫ߰ᾭˮƽҪáWCDû
вЩۡ

һĵطӵٶԶڽӵٶȡҲ
һӡ󣬺˵ΪӵΣвӡ
ίԱᣨUSCOLDйίԱᲥ˵ƬĴӡֱ
2000ף֤ЩֵĹ۵ǲǡġҲǲֵġ
˹工ˣ

ġʵܽǰڵ⡣

ûἰԽԷǴġġ
һ棬ǻһЩúܺܵĻͶ߿϶Ӱ˱
׼̡䣩 ˮίԱĽˮ磨ĿǰˮԼ
ռԴ20%Դ̫ܡԼȣڶʵ֣
ֽ׶ЩԴԶδܶȫԴκξصӰ족˹

ûˮͲܱ֤ĿǰĳˮһҪ
ʵˮίԱıвûеõӦеǿӡĿǰĹˮ
󣬴ӺˮΨһеѡԤƵҶ˿ڵ
˹

WCD̫ܻܡַǳ뻯
;ûпɱԡڿ͹ۡоЩʱ뿴ǵĹ
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ܵվӦҪҪǣ޷ˮ
һ֮ԴЩңˮӰ죬ζŲô
ˮˮũҵȺ͹ˮΨһѡ񡱡ʿִ·
·˹Ǻʵֵġ·˹ձίԱᣨJCOLDţ
ӽ͹ǽˮʳԴͺˮЧֶ
֮һձñиԭռӦǲʵġñ˵
ӡǣֹ۵Զʵ硱ί

 WCDձΪӹ滮ͽ26ָ룬ںܶ෽涼δ
ֿǸͷչ׶ΣģҪйҺ͹ʽ֯
ѭWCDָǲġҲǲܽܵġWCDԭʵϽֹͣ
κδӵĽ裬ҵķǱȻġй

塢𺦷չйҵ档

WCDԴЧʧȱ㹻ĽͣĿǰȺ
Ҫͣ̽衣һԷչйġʴίԱᣩ

˵ñǿӵĸЧӦƫطȫ
ĴӽĿίԱޱҪͼ⣬
ԼĻְ⣬һҪǣһЩˮԴд
ȵλĹѾԼҵˮԴʽӽ100ƪƫ
ۿܻ谭չйƶˮԴƻʵʩ磬ӡȡ
䣨ֻ30%Լйȡ䣩ӶǷǳҪģ
ΪǲĲƸͽйףǻΪ޸
ˮƻð취ɺˮɵƻءׯڣ
ҰֲȻЧĿƺˮͻ;õ
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Ҳ˵J.D.ѧʿ˶ʿǲʿѧλ



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ȻĳЩͬͶȡɵĻ᣻ڶѲͬϵͳѧλӲԷȥǹǣ
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ҽѧԺҵһЩԺϰϰԼΪ M.D.
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ԺѧλǸߵȵѧλAdvanced DegreesӽЩѧʵķ
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ʵġȻJD ͷѧʿĲϾûпȺͲĲ

Ҫ׼ȷطһһҪ̵ʹ׼ȷԣҪע
ǰĴͳ棬Ҫ㷺ؽ̵Щ¸׼ȷں

һҪ׼ȷJDӦ÷ɡѧרѧλ MDӦǡҽѧרѧλ
Զģ֮Զûж˻ŵĳƺɡΪǨʹͳ
ֺеĸJDԳΪɲʿڡѧʿ
JSDҲΪʾJDĿʵɣJSDĿоѧMDǿԽ
ҽѧʿͬʱMDPhD˫ѧλĿԽСҽѧxxѧѧ
ʿDMScһûϵһ˻ùѧλˣ
Լҽѧѧʿˡ

ȻܹͨJDͬJSDй˾һ㲻ɲʿ
ѧʿ

򹲺͡УɽڵһμºͿΪʱҽ˵
ҽģҽѧʿ..."

(XYS20050313)

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J.D. ʲôѧλ

ߣtianxin

J.D. ѧʿѧλ?

ѧԺҽѧԺְҵѧУ (professional school) ѧƺ
ѧԺྶͥѧԺѧλܶӣŽʮķѧԺĸ
ѧλƱ䶯Ҳܴԣǲܹ򵥵ĽѧԺѧλר
ҵѧλߺͼʮǰķѧԺѧλ͹ڷѧԺѧλ
϶Զԡ
ѧԺPre-law ǷѧԺ㼶͵һѧλһΪѧ
Ԥơ˵ӡƺһѵ࣬ʵPre-lawһ
ıѧλбҵԺҪԼѧϰſԱҵҵʱõѧʿ
ѧλ (Bachelor)J.D.ڷѧԺPre-law֮ϵһѧλ J.D. ѧ
ѧͳһΪgraduate student undergraduate studentܵ
Ҳgraduate student Ĵ ˽ѧλΪjuris doctorΪ
˰һıѧλ ʴ, Ϊڽ֮Ϊ ʿ
޲֮
ҲΪΪJ.D.ѧλֻҪ꣬J.D.ܳƲʿѧλ˵
ûиݵġʵвٹƵĲʿѧλҲֻҪԺٶͿ
õġʵΪJ.D.żߣѶȴ󣬺ܶJ.D.ѧڽ
ѧԺ֮ǰѾõ˶ʿʿѧλھһӡ
νJ.S.Dѧλ, ֻǽʮѧԺһ۷ѧѧλ. Ҳ
ֻй, Ү³ѧ, ޼ѧԺĽں
ԺķپֻJ.D.ѧλ

J.D.ʲôѧλ

ߣ

J.D.M.D.һνרҵfirst-professionalͷΣѧacademic
ͷΡʹﲢûжͷȷ֣ĵġʿһ
ȻָĺߡҲǱ뾭ʸԡдȽ׶Ρ

˵Լǡʿѡˡͼ󵼶Ŵˡʿһѧ
ʿɡ

J.D.걾ƽ֮ϵѧλʵѧԺѧоҲʵ
ⲻ֤J.D.ͿԵͬڲʿбҪJ.D.һıѧλ
Ϊߡŷ޵ĴͳҪϰϰҽѧҪбȽϷḻ
ⲢʾͲǱѧλJ.D.ڳΪѧʿLL. Bһ
ʵ˵Ǳѧλ޷ΪJ.D.֮LL. M˶ʿѧλ

ݡΤϷѧǵ䡷 Merriam-Webster's Dictionary of Law 1996Juris
DoctorһJ.D.ǡѧԺ䷢һѧλ

The lowest degree conferred by a law school

ȤĿԿӣԭķǳ̣

http://www.answers.com/topic/juris-doctor

J.D.1969ȡLL. B. ΪѧԺ䷢ġѧλfirst
degree

µһWikipediaȽϳҲø塣ҲᵽJ.D.Doctor
רҵͷΣM.D.ͬйӦÿĻ
ˡJ.D.ϡڷӵĳ̶ȣѾJ.D.ѧλ˻᲻ȥ
LL. M.ϡJ.D.ۣԼJ.D.˵ȡᣬJ.D.ѧλڷѧ
ԺĿ͹۵ȼ޹أͽѧԺ֮ǰʲôѧλ޹ء

Ȼ˽֪ܽķѧԺѾǳĲףܽķѧԺ
ϼѡJ.D.Ҫ϶ĳЩרҵPh.D.Ҫࡣʵ
ʵJ.D.ǱѧλͲӲ˵Լǡʿʹֻ˵Լ
ǹѧʿһȻ𾴡 

ֵĽͿJ.D.

ߣtianxin

, J.D.Cadidate graduate student,undergraduate 
studentȤȥһJ.D.ѧֵĸ: the 
law degree granted upon graduation by many university law schools with 
accepted high standards of admission and grading. This often 
supersedes the Bachelor of Laws in recognition that the law curriculum 
entitles a person to a graduate degree. 
(http://dictionary.law.com/definition2.asp?selected=1073&bold=||||)

һνͽѧԺƵʷ, ǿԿJ.D.֮Ժȡ
L.L.B. ΪϿɡѧԺӦѧõоѧλin 
recognition that the law curriculum entitles a person to a graduate 
degree.˵һʿͷβһĳνһٷϿɵ
оѧṩֵĽʵҲJ.D. Ǿ
post-graduate law study õJ.D. is an abbreviation for the 
Latin Juris Doctor, also called a Doctor of Law or Doctorate of 
Jurisprudence, and is the law degree typically awarded by an 
accredited U.S. law school after successfully completing three years 
of post-graduate law study. Generally, a 4-year undergraduate degree 
is required to be eligible for entry into a J.D. program.

˵ΪJ.D.ǷѧԺfirst degreeֻһƵѧλ
Ϊfirst degreeֻ˵ڷѧԺڲJ.D.һֻѧλfirst degree
ͬڱѧλһundergraduategraduate綨ƺо
ѧλfirst degree  second degreeʵϹJ.D.õ
ѧԤƵѧʿѧλͬѧλΪǰġ

ΪѧλӦѧλı׼֪ǿй
ߵı׼һͱ׼60ѧλ׼񶨼ʮ
ѧλ׼ʱƣ䷨ӡȻ֮Ϊʿҹ֮
оǻҪǿʿJ.D.ѧλΪѧʿǲһ㴵ë
ˣ


J.D.ʲôʲô

ߣBerkeleyWolf

ҿJ.D.ڹڵѧԺ˶ʿѧλ

http://www.answers.com/Juris%20doctor

In the U.S., according to legal convention, the J.D. degree does not 
confer the title of doctor.

The LL.M., "Master of Laws", is a post J.D. degree

Doctor of Juridical Science (J.S.D.), Doctor of the Science of Law 
(L.Sc.D.), and the Legum Doctor or Doctor of Laws (LL.D.) confer the 
academic and social title of "Doctor," but is rarely used by 
practicing lawyers in the U.S.

J.D.ʲôʲô

J.D.һְҵѧλĿͷְҵʿ
J.D.Ǵ·ְҵĵһѧλ
J.D.Ƿѧĵһѧλѧλ
J.D.Ҫ˱бѧ
J.D.Ƿѧϵеѧʿѧλ
J.D.ѧΪоԴ
J.D.Ҫύʿģд硣
J.D.һʿͷΡ
ѧλȼϣLL.MJ.D.ߣJ.S.D.L.Sc.D. LL.D.LL.M.ߡ
ͲʿѧλͬJ.S.D.L.Sc.D. LL.D.J.D.

ܽ᣺
J.D.ǻרҵ֮ķѧĵһѧλJ.D.ڷѧ
ϵڱѧλȻѧϵеıѧλҪѧƵı
ѧλ֮롣


J.D.J.D.


J.D.M.D. ɷΪʿ

ߣtianxin

1. J.D.о (о)

2. ѧԺĵλ൱оԺԷѧԺĻѧλܵͬڱ
ѧλû˽J.D.candidateundergraduate student.

2. J.D.M.D., professional doctor,research doctor(While the 
Juris Doctor is a professional doctorate, similar to the Medicin?? 
Doctor (Doctor of Medicine).

3. J.D.ǻ÷Ԥѧʿѧλѧʿѧλһѧλ

4.ڵķѧѧʿJ.D.ȫ¡ԹڵķѧѧʿԳ
ʿĻڵҽѧѧʿԳƲʿԳΪթƭ 
J.D.عͱ뽫ѧλԳΪѧʿ

5. ѧУѧʿѧλĻԻѧλ֤ϰֵֽע
J.D.ѧλֻ֤вʿûѧʿ

6. õJ.D.Լֺע J.D. (ʿ), bachelor 
of law.

7. ʦһ㲻ụƲʿ, ҪΪͳ, Ϊݹ涨J.D.
ִҵ, ԴҶǲʿ, Ʋʿ岻ֵϵǣJ.D.
һM.D. ͿͬǰƲʿˣΪжԣ
ۣM.D.  J.D.ҲܳƲʿΪM.D.P.h D.

7. J.D.Ӧѧλı׼ǹڵı׼ĳ˵ı
׼

8. ڵ˰J.D.Ph.D.,ǵ⡣û˾Ҫ
ԽΪѧʿ

֮ʿƼоʣJ.D.ѵΪʿ
J.S.DȫΪѧʿ򷨿ѧʿ


ѧʱ˵JDӦɷѧʿMDӦҽѧʿ

ߣxj

ǶǿƾJDMDfaculty, һ㶼Ϊְҵоѧλ˶ʿ
Ҫߣ൱PhDresearch oriented.

JDɷѧƣй˵ĸпķѧǲǵҲԳJD

ôйҽѧأǲǿԳMD 


I think many people here missed a very important point:

ߣsteven

both J.D and M.D holders are qualified as professors in the U.S 
professional school. Look at Yale, UCSF, or just any place, look at 
their law school and medical school. Althought many professors there 
have Ph.D degrees, and many of them, in fact, a very significant 
number of them holds J.D/M.D degree without Ph.D. I think it is 
irrelevent here to discuss what J.D should be translated. These people, 
with J.D and M.D degree teach in the world class universities in both 
research and or other areas, that says all if you really care about 
this J.D/M.D qualifications.

(XYS20050313)

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ŷƴӸС



ŷաƴӸС˵ġϰԵù߶
ʹ߱ȥµĻôƶƴϵͳĿ
ûпʵ֡ƴϵͳǺ󻰣ȱҪȷ
Ҫϵͳʲô

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dƴϵͳ

ϵͳѧϵͳƴϵͳѧϵͳѧϵ
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뺺ƴ֡XYS20050302Ҽ򵥵г˼֤ݣа
jiujiouݡӣ֤ƴǺϵͳŷ
ٳģۨҲһܺõ֤ƴӡyuyuan
ҪǵĻӦΪۨݣۨanݡҪ󣬣ۨݲһ
ñһñyҲǶġƴ涨дΪyu
yuanֻϵͳеͨʷӲԶĹƶ
ϵͳʱyڱΣԼèӦáñ
ԲñֻҪ֤ʷ涨ˡƴ
GBT161591996õϵͳ׼ĹԺƴ
ϵͳϵͳϵͳĿȷ֮󣬲ܰѧ
Ҫȥηִдʹױдμ׹ɣʹ
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£ȥ޸еĺƴͽ͵ģΪ˰Ѻƴ귽
޶˰ַ޶Ͳ֪Ǹ޶
޶γɹ˵˵ΪĳƤ档

йISOӦϣе׳ֵꡱԱʹ
ꡱһ𣬲һʹںתдɣ
ֻص꣬תֵ룬ʹͷתͷԡ
ѾĻذ˵˼ңˮΪľǲƴ
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ûй˻躺ƴߡ47겻֪ɶһϹѾ
ȥΪôִݣ̣ȨϵĽ
ڷӵغգ

ϣƪʹŷѺƴֿףԲ
ԡƴӸСո֡

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廪ѧZhixin Ba, Haichang Zhou, Huai Zhang and Zhenxiao Yang IEEE

BerkeleyWolf

ϸȽһƪIEEEϵ¡µΪ廪ѧ
Zhixin Ba ,Haichang Zhou ,Huai Zhang and Zhenxiao Yang2000 The 
Fourth International Conference on High-Performance Computing in the 
Asia-Pacific Region-Volume 1 Ե·1994 Scalable 
Parallel Libraries ConferenceNatawut Nupairoj and Lionel M. Ni
2000ǱȽϡ3ҳ1994ǱȽܼ8ҳУδ 
2000£Ϊxysʽ޳ȥͼ͹ʽΪȫġ
ӡ1994£Ϊ2000¶Ӧ֡ΪPDFתTXTޣ
𵥴ʿ


¼Ѿͨʼ֪ͨȻѧLionel M. 
Niڡ (http://www.cse.msu.edu/~ni/)

 anarch 緢ֱϣMITBBSϡлXYSĶChen
(δɣʲṩȫ)ṩƪµĵı

Performance Evaluation of some MPI Implementations
on Workstation Clusters
Zhixin Ba ,Haichang Zhou ,Huai Zhang and Zhenxiao Yang
High performance computing center
Cernet, Tsinghua University, 100084
bazx@chpcc.edu.cn

http://csdl.computer.org/comp/proceedings/hpc/2000/0589/01/05890392abs
.htm
The Fourth International Conference on High-Performance Computing in 
the Asia-Pacific Region-Volume 1
May 14 - 17, 2000
Beijing, China

Performance Evaluation of Some MPI Implementations on
Workstation Clusters *
Natawut Nupairoj and Lionel M. Ni
Department of Computer Science
Michigan State University
East Lansing, MI 48824-1027
{nupairoj, ni}@cps.msu.edu
http://ieeexplore.ieee.org/xpl/abs_free.jsp?arNumber=376999
Scalable Parallel Libraries Conference, 1994., Proceedings of the 1994


Abstract
Message Passing Interface (MPI) has already become a standard of the 
communication library for distributed-memory computing systems.
Message Passing Interface (MPI) is an attempt to standardize the 
communication library for distributed-memory computing systems. 

Since the release of the new versions of MPI specification, several 
MPI implementations have been made public available. .
Since the re-lease of the recent MPI specification, several MPI 
implementations have been made publicly available.

Different implementations employ different approaches. It is critical 
to selecting an appropriate MPI implementation for message passing 
based of communication is extremely crucial to these applications.

Different implementations employ different approaches, and thus, the 
performance of each implementation may vary. Since the performance of 
communication is extremely crucial to message-passing based 
applications, selecting an appropriate MPI implementation becomes 
critical. 

Our study is intended to provide a guideline on how to submit a task 
and how to perform such a task, economically and effectively, on 
workstation clusters in high performance computing.

Our study is intended to provide a guideline on how to perform such 
a task on workstation clusters which are known to be an economical and 
effective platform in high performance computing.

We investigate several MPI aspects including its implementations, 
supporting hardware environment and derived datatype which affect the 
communication performance. In the end, our results point out the 
strength and weakness of different implementations on our experimental 
system.

We investigate several MPI aspects including its functionalities and 
performance. Our results also point out the strength and weakness of 
each implementation on our experimental system. 

1. Introduction
In our study, four popular MPI implementations, shown in Figure 1 , 
are considered. Our testing environment is based on IBM SP2 system 
interconnected via both Ethernet and high performance switch. The high 
performance switch can provide up to 1 OOMbps per channel.

Our testing environment consists of 6 DEC Alpha workstations 
interconnected via both Ethernet and a DEC GIGAswitch. The DEC GIGA 
switch can provide up to 100 Mbps per channel. 

Figure 'I. The model of the communication modes

identical to figure in 1994 paper: Figure 1. The model of the 
communication modes

We have developed a set of benchmarks to evaluate the performance of 
both point-to-point and collective communication services. These 
benchmark programs include:

We have developed a set of benchmarks to evaluate the performance of 
both point-to-point and collective communication services. These 
benchmark programs include: 

1. Ping: to measure the peak performance of the point-to-point 
communication over a communication channel;

1. Ping: to measure the peak performance of the point-to-point 
communication over a communication channel; 


2. PingPong: to evaluate the end-to-end communication latency which 
include the effect of the communication protocol;
2. PingPong: to evaluate the end-to-end communication latency which 
includes the effect of the communication protocol; and


3. Collective: to evaluate the performance of some collective 
communication, including broadcast, and barrier synchronization.
3. Collective: to evaluate the performance of some collective 
communication, including broadcast, and barrier synchronization.

The rest of this paper is organized as follow. In section 2, we 
discuss the model and performance metrics used in our study. Section 3 
introduces experimental results. In Section 4, we conclude our paper.

Due to space limitation, only partial results are presented in this 
paper.
Due to space limitation, only partial results are presented. 
Interested readers may refer to [6] for additional performance results. 


2 Model and Metrics

3 Model and Metrics 

2.1 Measurement Model

3.1 Measurement Model

Figure 2. The model of the communication

identical to 1994 paper: Figure 2. The measurement model 

2.2 Performance Metrics

3.2 Performance Metrics

We compare with our program benchmarks on different communication 
models. We also focus on the difference of communication performance 
of different communication models. The following two metrics are 
sufficient for the evaluation.

Comparing two communication systems requires measuring several 
metrics. In our study, we compare the implementation of different 
communication libraries. Thus, only two metrics are sufficient for the 
evaluation.

Communication latency (t)
The communication latency (t) is defined to be the time that a process 
spend when it sends or receives (or both) a message. The communication 
latency is proportional to the message size, which is given by

We define the communication latency (t ) to be the time that a 
process has to spend when it sends or receives (or both) a message. 
The communication latency is proportional to the message size which is 
given by 

t = t_s +n x t i +[n /p] J X t_p (1)

t = t_s +n x t i +[n /p] J X t_p (1) 

where t, is the start-up latency which is fixed for each message, n 
indicates the size of message, t, is the transmission latency (usually 
much less then t_s), and t_p, is the packaging latency. The start-up 
latency also includes the fixed cost of system call and initialization 
overhead.

where t , is the start-up latency which is fixed for each message, n 
indicates the size of the message, t t is the transmission latency 
(usually much less than t S ), and t , is the packetization latency. 
The start-up latency also includes the fixed cost of system call and 
initialization overhead. 

Channel throughput ( p)
Channel throughput (p ) or bandwidth is the rate at which the network 
can deliver data (usually in Mbits per second). It IS widely used 
among the vendors because of its simplicity. We use this metrics when 
we compare the performance of different message sizes. The throughput 
can be directly computed from the communication latency by

The channel throughput (p ) or bandwidth is the rate at which the 
network can deliver data (usually in Mbits per second). It is widely 
used among the vendors because of its simplicity. We use this metric 
when we compare the performance of different message sizes. The 
throughput can be directly computed from the communication latency by


/####### formula 2 is omitted here ########### (2)
identical formula 
if we substitute t with Equation (1 ), the throughput becomes
if we substitute t with Equation (1 ), the throughput becomes 

/####### formula 2 is omitted here ########### (3)
identical formula 


So the peak throughput will be limited to (10^-6)/t_t when the message 
size is infinite.
Thus the peak throughput will be limited to (10^-6)/t_t when the 
message size is infinite.

Furthermore, the maximum throughput that can be achieved is defined as 
the sustained throughput.
By sending messages as fast as possible, such as in the buffered mode, 
we can compute the sustained throughput form Equation (2).
We further define the sustained throughput as the maximum throughput 
that can be achieved. By injecting messages to the communication 
channel as fast as possible, such as repeatedly sending messages in 
the buffered mode. we can compute the sustained throughput from 
Equation (2 ).

2.3 Communication Parameters
3.3 Communication Parameters

There may be relationship between some communication parameters and 
communication performance. The communication performance can be 
greatly improved when appropriate values are set for the parameters. 
In our benchmarks, we focus on two parameters: message size and the 
buffer size.
Some communication parameters may have dramatic impact on the 
communication performance. The
communication performance can be greatly improved when appropriate 
values are used for the parameters.
In our benchmarks, we study two major parameters: message size and the 
buffer size.

3 Experiments
3.1 Testing Environment
In our study, we perform our experiments on workstation clusters of 
IBM SP2, which consists of 28 RS/6000 nodes interconnected via network 
and high performance switches, including 4 broad-nodes with 512 Mbytes 
of main memory and 24
narrow-nodes with 256M Bytes of main memory. The parallel programs are 
performed on the narrow-nodes. The Operation System is AIX 4.1.5.


3.2 Experiments Results
In this section, we mainly present the results from our experiments 
and then analysis these results. Each data-point in our results is 
average of 10 testing data. More exact to gain, the maximum length of 
messages is 10 Kbytes.

Figure 3. Sending Latency (short messages)
4 Conclusion
7 Conclusion

In this paper, we discuss the performance of some MPI implementations 
publicly available on workstation clusters. From the analysis, we can 
figure out that the software overhead is very high and it plays very 
important pole on improving the overall network throughput.

In this paper, we discuss the evaluation of some MPI implementations 
which are currently publicly available on workstation clusters. Our 
results indicate that the software overhead is very high and has to be 
greatly reduced in order to fully exploit the bandwidth of the 
high-speed switch. 

Among all these implementations, we suggest you selecting the buffered 
mode as the best communication mode on IBM SP2 machine, because this 
mode can efficiently employ the bandwidth of high performance switches, 
so as to improve the overall programs communication throughput. 
Certainly, choosing this communication mode, you should be carefully 
because this mode requests a lots of memory.

If the communication is between end-to-end, we can replace the 
standard functions with sendrecv function, so as to simplify the 
program and to prevent communication from deadlock.

Since the space of this paper is limited, we cannot discuss the 
situation which performing end-to-end communication with non-blocking 
communication function rather than with blocking functions. Moreover, 
some other communication modes MPI provided, such as non-contiguous 
datatype and pack/unpack, will be discussed later.

Because of time limitation, we could not conduct an extensive set of 
experiments on different distribution of non-contiguous datatypes. But 
our initial results based on simple vector datatype show that the cost 
of sending non-contiguous datatype is not much higher than sending 
contiguous datatype of the same size. Further investigation on the 
impact of the noncontiguous datatype is needed. We are also 
investigating the performance of other collective communication 
services. .


References
1. M. P . I. Forum. MPI: A Message-Passing Interface Standard. Mar. 
1994
2. B. Gropp. R. Lusk. T. Skjellum. and N. Doss. Portable MPI Model 
Implementation .
Argonne National Laboratory, July 1994
3 , H I Nupairoj and L a N i p " Performance evaluation of some MPI 
implementations I Tech. Rep I MSUCPS-ACS-94. Department of Computer 
Science . Michigan State University, Sept I 1994

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¥˷Ļ

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ʼбxys_friends@yahoogroups.com

ù䶩ġù䣬ܿ޷յ
Ƽ䣺yahoo.com.cn, yahoo.com, hotmail.com

ġ˿ʼбĵ䷢һհż

xys-subscribe@yahoogroups.com 

塢ͣ˿ʼбͣ䷢һհż

xys-unsubscribe@yahoogroups.com 

Ͷxinyusi@yahoo.comôıļͶ塣

˿(www.xys.org)(xys.dxiong.com)(xys1.dyndns.org)(xys.3322.org) 


