Compiler back end design for translating multiradio descriptions to operating system-less asynchronous processor datapaths

Size: px
Start display at page:

Download "Compiler back end design for translating multiradio descriptions to operating system-less asynchronous processor datapaths"

Transcription

1 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY Comler ak ed desg for traslatg multrado desrtos to oeratg system-less asyhroous roessor dataaths Daraya Guha Cetre for Hgh Performae Emedded Systems, Nayag Tehologal Uversty, Sgaore Emal: guha@tu.edu.sg Thamlla Srkatha Cetre for Hgh Performae Emedded Systems, Nayag Tehologal Uversty, Sgaore Emal: astsrka@tu.edu.sg Astrat Most asyhroous roessor Istruto Set Arhtetures ISA) are ased o a sgle tye of uderlyg asyhroous rut desg style. Asyhroous roessor ISAs are etrely deedet o the tye of asyhroous desg style hose ad a suort a lmted set of smle alatos oly. Desg reuse s tyally dffult to realze suh ases. I ths aer, we show a ehavoral model of a redtor rut system that ofgures a alato rofle-drve asyhroous roessor ISA omrsg two asyhroous desg styles. The redtor rut system s used to traslate alato rofle ad mult-rado ode to the roessor dataath through a omler ak-ed. The target s a asyhroous roessor that does ot ru a oeratg system ad s used oth as a omlemet ad alterate to software-defed rados wth hgh degrees of desg reuse. Idex Terms asyhroous roessor, ISA, redtor rut, mult-rado, omler ak-ed, desg reuse I. INTRODUCTION Commo asyhroous roessors uderlyg desg styles lude DI uas-delay Isestve) [1], STAPL Sgle Trak Hadshake Asyhroous Pulse Log) [2], ad STFB Sgle Trak Full Buffer) [3] self-tmed rut famles. The asyhroous roessor Istruto Set Arhteture ISA) s etrely deedet o the asyhroous desg style tye ad erformae metrs lke dataath erformae ad rah redto for mult-level strutos rema dffult to e streamled for multle sets of alato rofle tasks. Ths aer targets asyhroous roessors ased o a hyrd of asyhroous desg styles DI ad STAPL), where reofgurato the rut omoets of uderlyg asyhroous desg styles a take lae ased o the alato rofle. Ths aer further desres the ehavoral model of a redtor rut system that a traslate alato rofle ad rado rotool ode to the asyhroous Based o Reofgurale Frame Parser Desg for Mult-Rado Suort o Asyhroous Mroroessor Cores, y Daraya Guha ad Thamlla Srkatha whh aeared the Proeedgs of the IEEE Iteratoal Coferee o Comutg: Theory ad Alatos, ICCTA 2007, Platum Julee of the Ida Statstal Isttute, Calutta, Ida, Marh IEEE. roessor dataath dretly through a omler ak-ed. Ths desg methodology serves two uroses: 1. hels maage omlex ode mag oto roessor dataaths the asee of a oeratg system, 2. mroves uo asyhroous desg omler ak-eds geeratg hyrd asyhroous desg style hadshakg ruts y ororatg alato rofle ad rado rotool module fte state mahe exeutos) odes a sgle framework. Ths aer s arraged as follows. Seto II dsusses the desg aroah of a hyrd asyhroous roessor that suorts mult-rados the asee of a oeratg system; Seto III dsusses the arthmet of evet sequees asyhroous dataath models, Seto IV shows the system ehavoral modelg math of the redtor rut, Seto V shows the evaluato of the redtor rut system, Seto VI shows the evaluato of the omler ak-ed desg ad Seto VII rgs aout the oluso. II. DESIGN APPROACH OF A HYBRID ASYNCHRONOUS PROCESSOR SUPPORTING MULTI-RADIOS WITHOUT AN OS Hadsets ad ortale osumer eletro deves tyally eed to suort dverse alatos ad usually rovde multle rado hoes for ommuatos. The mult-rado hoes are usually maaged y the oeratg system through drver swthg amog the dvdual rotool Network Iterfae Cards NIC). I the asee of a oeratg system ad software maagemet of rotool modules, the roessor must e ale to suort these rado rotool modules whe voked y the alato. Tll ow, the oly rados that are suorted o oeratg system-less asyhroous roessor ores are small-szed rados lke TR1000 [4,5]. It s very dffult to ma large omlex rado staks otmally oto the asyhroous ore, rado rotool desrto laguage traslato eg a maor ottleek. The asyhroous ore ad dataath s derved out of a sgle tye of asyhroous desg style ad realzg rogrammalty reofgurale style selet ased o rado-ased alato roflg s very dffult.

2 8 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY 2008 I the asee of a oeratg system, the maor hallege eomes to desg effet mro-arhtetures that resod to exteral terruts geerated y hgh-level desrto laguages. Alato odes ad rado desrtos are frst rofled to detfy ommo futoal modules a mro-arhteture aware maer, so that the roessor dataath a e ofgured exatly the maer as t would e f a software terrut was voked y a oeratg system. A redtor rut system forms a key omoet of ths mro-arhteture aware traslato of rotool ad hgh level desrto laguages to the asyhroous roessor dataath. Most of the urret emodmets of asyhroous roessors usg reshuffled ommuato roesses eled asyhroous ruts are ased o DI rut models [1]. A dffulty wth DI desg suortg artrary frequet hages the alato rofle s the dffulty satsfyg the requremet of orret workg of the desg resee of uouded oerator delay varaes. Esurg the roerty that the asyhroous roessg etty the roessor struto set) does ot get loked to a artular rado rotool, t s mortat to esure that there s a mehasm to swth over the rado mode after a self-ferred tme terval. For DI, f ths s to e aheved, heker ruts to detet ourree of trastos as rado rotool staks that are hadled f a oeratg system s reset) are eeded eve though they would hae ayway. Ths a e overome y STAPL ruts that elmate the akowledgemet ad data reset hases of the four-hase hadshakg rotool used DI ruts. I ths aer, a hyrd DI-STAPL desg style roessor dataath has ee osdered. The redtor rut system s also omrsed of ths hyrd desg style, ad ehavoral modelg has ee arred out to oform to the arthmet of evet sequees asyhroous dataath models. III. ARITHMETIC OF EVENT SEUENCES IN ASYNCHRONOUS DATAPATH MODELS LAD Legth Adatve Data) [4, 5] s ommoly-used arthmet modelg evet sequees asyhroous roessor dataaths ad struto set arhtetures. Ths s a artularly useful arthmet log where t-seral struto set arhtetures s tued le wth the legth adatve data words. Ths roosto s extremely useful for mlemetg desg reuse asyhroous roessor ased latforms. Curretly, LAD arthmet axoms suort oly oe task at a tme, ad do ot allow data terleavg or delmter re-assgmet. A few extesos of the LAD arthmet axomat foudatos to lude smultaeous ourret mult-tasks y ollaoratvely re-assgg delmter LAD dgts A delmter t s a t uo whose ourree, all the leftmost t ostos are take to e of the value of the delmter t) has ee show [6, 7]. Earler fds [6] have suggested ehag LAD arthmet the otext of odetermst data-flow omutato for ollaoratvely assgg delmter LAD dgts. Ths s a system desg hallege eause t volves o-determst dataflow omutato ased o the fat that data arrvg should e roessed mmedately) ad omutatos wth artrato for qualty-of-serve rortes), whh makes the usual LAD arhteture emodmets related asyhroous roessor desgs dffult for arallel re-overso ad otmzed LAD arthmet maagemet. Delmters a our aywhere wth a data word. A examle of ths stuato s that a adder may eouter , where 1 s a delmter t. The result should e a sgle 1, ad ot 1111, whh s wastage of eergy for roessor dataath omresso. Ths rolem s eve more rooued for odetermst data-flow omutato mas that are a evtalty of mult-rado suort asyhroous roessors, rmarly due to artrary rado voatos ad data terleavg. Ths work s urretly eg further studed ad we reset some of our tal fds o addressg ths ssue through a system ehavor model of a redtor rut that mas alato tasks to the roessor dataath through multle rado lass lkage assoatos. IV. SYSTEM BEHAVIORAL MODELING MATH OF THE PREDICTOR CIRCUIT The system ehavoral model of the redtor rut s ased o the followg assumtos: 1. Alato tasks are radomly dstruted ad a our at ay tme ay tye of alato a request a serve at ay tme). 2. A rado s voked y a alato the alato that wats serve wll eed to e ommuated). 3. A rado a e voked y multle alatos at the same tme the same rado may e used ommuatg multle alatos wth a requested qualty of serve smultaeously). 4. Multle rados are eessarly voked y multle alatos at the same tme multle rado terfaes are reset the ommuatg deve). 5. The assoato of alato task o roesses to rado lass lkage sets s stataeous. Rado voato s doe stataeously the deve as soo as a alato arrves for ommuatos. Ths s doe loally ased o guaratee of qualty of serve ad to suort the roessg ad ommuato aaltes of that alato). 6. Alato task o roesses a shft aross rado lass lkage sets. Ths meas that the tasks a e arttoed ad loally assged to a omutg grou ad-ho ased o the ature of omutato smlarty). 7. Prorty of the task o roesses geerated y multle alatos may hage durg the roessg stage. Ths s to aommodate alatos that may eed more tme-rtal resoure-ased roessg. Followg ot 6, ths also meas that there s rovso to loally

3 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY hage the task o roess rorty assoated wth a artular rado lass lkage set. To guaratee qualty of serve, f a alato s advertsed usg a rado tye for whh the hael s degraded, the alato may start to e advertsed usg a dfferet rado o the same hysal hael ut dfferet erformae haratersts) 8. Tasks searated to sets voked uder dfferet rado lkage sets may e shfted terally wth the set grous. Ths s to esure that eve f the otrol hael odto hages, data are stll ommuated wth the qualty of serve requested aross dfferet rado meda avalale. Ths s a loal oly ad teral to the redtor rut for helg hoose the rado selet for ommuatg) 9. A alato has to e mmedately roessed ad aot e uffered Wthout a oeratg system ad wthout sgfat terrut hadlg suort, the tasks would eed to e exeuted as soo as they arrve to revet rado lok- ad degradato of qualty of serve). A. Mathematal assumtos 1. The rado lkage lass sets that serves alato task o roesses s osdered to form a dmesoal vetor sae. 2. The mathematal reresetatve values of the redtor rut system resoures are ostraed to the rage of 0, 1). Ths meas that the redtor rut system hadlg a artular tye of alato vokg oly oe rado lass lkage set s rereseted y 0,0,0 ) o load ostrat) ad the odto that t mas multle alatos vokg all the rado lass lkage sets s rereseted y 1,1,1,.), sgfyg a fully loaded ostrat. 3. The otmal ost futo for task admttae aross dfferet rado lass lkage sets sas over ths dmesoal vetor sae. 4. The dmesoal vetor a e used to desre the urret state of the redtor system, ad the orm of ths vetor forms the ass of the rakg of the redtor rut load term of rado lass lkage set assoatos. 5. For tryg to make the rolem of mult-alato task o roess alloato aross all rado lass lkage sets ad su-arttos of the vetor sae NP hard, os are desred ad raked usg the same omutato resoure requremet dmesos. Jos a e added ad sutrated from the redtor system state vetor. 6. The system ehavor of the redtor rut s modeled terms of the ut futo that s a dual varale of rado lass lkage sets ad resoure demad from a alato task o roess. B. Tehques for alato s serve request task o ft aross the rado lass lkage sets Frst Ft: Partto the vetor of rado lass lkage sets equally amog all the alato tasks that requests serve Best Ft: Partto the vetor of rado lass lkage sets otmally ad shft task o roesses to that rado lass lkage set whh most losely fulfls the alato s serve request wth the least umer of os volved. Worst Ft: Partto the vetor of rado lass lkage sets ad shft task o roesses to that rado lass lkage set whh most losely fulfls the alato s serve request wth the maxmum umer of os volved. C. Predtor rut system load estmato terms of alato os roessed through rado lass lkage set assoatos) ad roess o shft The load dstruto mehasm the redtor rut system reeves gloal state udates terms of alatos roessed ad rados voked) artrarly tme. Ths resets a losure rolem of the redto of the degree of assoatg a task to rado lass lkage sets as o mmedate feedak to a o laemet s rovded. Therefore the redto susequet to the frst eah tme frame are made wth data that s kow to e out of date, ad rolems smlar to those eoutered y the least loaded tal ft model may arse. Oe advatage of usg redted resoure requremets terms of roessed alato o tasks for dfferet rado lkage lass sets s that the same tral fttg tehque that s used to selet the dataath ma a e used to rovde a estmate of the system load after o shft ad laemet. Thus the result of the fttg omutato s used to dretly udate the load value stored for the dataath ma. Charatersts of the arttoed vetor lass model the system ehavor desrto of the redtor rut a e modeled uder ths assumto. A key ssue of the redtor rut system load estmato s the atual o shft of alato task roesses order of the rado lkage lass set assoato rorty volvg hage ogog task o exeuto rorty status. The other ssue s the resoluto of rorty oflts for tme-rtal ad o-tme rtal tasks where the level of rorty s suet to hage. Mathematally, ths meas that the vetor sae arttog wll hage ad dmesoal reresetato mght ot rema the same. D. Mathematal modelg of the redtor system target mahe omlato ut) Let = The alato task orresodg to rado lkage lass set ; roess orresodg to lass. E = Set of elgle roesses,.e. the umer of tasks that a e shfted amog rado lkage lass sets = Exeted roess lfetme,.e. the tme tll a roess fshes exeutg C = Cost of shftg the roess amog rado lkage lass sets k = Normalzato ostat. e E

4 10 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY 2008 The,,. *... 1) Let E ff, = Codto of redtor system at tme t t ) k, terms of the rado lass lkage ouay vetors., for = Jo the redtor system at tme t t ) shftg the task roess amog rado lkage lasses. Fudametally, the otmzato rolem for omutg resoure alloato the redtor system for mag oto the roessor dataath would e: m ).. 2),.e. mmze the orm aross all the trasto roess vetors. The geeral seleto oly for o shftg aross the rado lkage lasses s thus gve y: max * ) e C. 3) There exsts a lesser tha the least feasle soluto terms of geeral dsrete GD) ost futos to a lass arttog rolem f the otmal ost threshold value s at least.durg the shft of alato tasks C MAX / stataeously over the rado lkage lasses, there remas to e show ad rove that there exst a feasle ost that s always attaed whh s lesser tha a least threshold value. Ths meas that the ost of trasferrg alato tasks of a artular rado lkage lass terally durg rado rotool laguage mag to the roessor dataath does ot overall redue the ealty for ufferg t wthout roessg mmedately. I order that the redtor system modelg for dvdual rado lkage lasses o a oe-to-oe ass holds, we shall show that the ost of trasferrg alato tasks aross dfferet rado lkage lasses suets the ehavoral modelg to e the same as whe the tasks are roessed dvdually y the redtor o a er-rado lkage ass. Let vetor sae x e a otmal artto aross E for some. The hysal terretato of ths s that the rado lkage lasses form a ovex futo set ad has a otmal artto aross the set of vetor saes saed y the rado lkage lasses. The dfferee s that these lasses are set statally. The ssue of NP-hardess omes to osderato f the sae saed y ad ehaves quas-statally at every tme whe there s a trasto amog the s. The questos to e aswered ths rolem formulato are thus: 1. Does there exst a otmal artto of a quasstat vetor sae V 1 for a elemet trasto defed from a ovex futo set F1 to aother ovex futo set F2 defed aother quas-stat vetor sae, V 2? 2. Is ths rolem NP-hard? Let us frst fous o the defto of the ovex futos aross quas-stat vetor saes. A futo s alled strogly ovex f for three ots x 1 ad x 3, the followg result holds: x2 x1 ) * x1) x3 x2 ) * x3) x2 ) x1 x2 x3 x3 x1.. 4) From 1), Let us ostrut a set P } { over some, the exeted roess lfetme. For a ouded, P wll e a ouded set MAX wth some least uer oud P u. 5) For the sets P ad P, thus we a hoose the trlets P P P x1 P P P x, x, x ) ad ) suh that equato 4) holds for eah of these trads o ther resetve doma sets.. 6) A futo F P ) a thus e defed to e ovex for P P P the trlets x1 ) aross P.Smlarly, a futo F P ) a e defed to e ovex for the trlets P P P x1 ) aross P 7) From the defto of equato 2), the vetor sae V ) sag aross the set a e defed as P P P the ass sa of x 1 ), essetally otg the fat that the odto of the redtor system at tme t t ) where t MAX ) s a ermutato of the elemets of P. From 5), eause of the oudedess of P, there exsts a futo F P ) whh a e C ermuted exatly to a ovex futo F suh that C P P P C F { x1 } ad V ) V F ). 8) C Smlarly from 8), V ) V F ) 9) From the defto of vetor saes,

5 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY V ) V ) V ) 10) V From the defto of equato 2), a sae ) sag aross the set a e thus defed o P P P the ass sa of x, x, x ), essetally otg that o of shftg a roess the set E aross the sae V ) for defed s a futo F P ) that mas the { } s to some elemets { } s for t [ t, t ] defed ad ouded y MAX.. 11) As { } are ermutato elemets of s, the result C from 11) ad 8) s that F P ) mas to..12) V ) s the a susae of V ) From equato 10) t thus follows that. 14) F..13) ad from 10) aga, m, ).. 14) Ths shows that a otmal artto of the quasstat vetor saes saed y the rado lkage lasses does exst. 15).E.D. We ow show that deed ths s a NP-hard rolem. Let us defe as the otmal artto of the quasstat vetor saes saed y the rado lkage lasses, ased o equatos 1) through 15). From 11) ad 13), t s easy to see that m ). 16) Let us defe a Vetor Sae V ow sag over ), draw from the elemets V ) ad V ) 17) From 13), we a say that, where s a salar. 18) We defe as { q }, where q 1, f mas exatly to, whh meas, there s erfet -order roessg of dvdual alato tasks wth all the dfferet rado lkage lasses. q 0, otherwse. 19) We a thus solve a suset rolem of set, derved fromv, over the elemets { q } ad a oud, suh q..20) that From the ost futo defto 1) ad the oly of o shftg aross dfferet rado lkage lasses equato 3)), we a say from Equatos 16), 17), 18) ad 19) as the fat that exst ff for whh q. 21) The hysal terretato of ths statemet s that the seleto oly hooses the alato tasks that artular rado lkage lass to shft for whh there s a maxmum the ost futo for shftg,.e. the math etwee the umer of tasks to shft mathes resely the umer of tasks assoated that rado lkage lass whh are eg maed oto the dataath y the redtor system at that stat of tme. Ths roves that the rolem for quas-stat vetor saes saed y the mult-rado lkage lasses s NP-omlete..E.D) Susequet to ths, we shall ow rove a more owerful relato reset to determg the otmal rado lkage assoato ost futo whe mag multle alato tasks to the asyhroous roessor dataath through dvdual rado lkage assoatos. Suose the set has elemets all. Let us also assume that the total set of all ossle rado lkage lasses s K. Ths s to geeralze the rolem more, the ratal osequee of whh s that more rados a e suorted the same latform through frmware ugrades, athes ad etrely ew software sutes for ewer rado stadards that may ome the future. Let the ost futo, as defed from Equato 3), o e " C. 22) The, the ost er eah rado lkage lass " C C K..23) / I the usual ase, the ost futo for alato task admttae to a artular rado lkage lass determes whh rado s voked for whh alato) s deoted yc. At ay ot of tme t MAX, there exsts some { q } for whh equato 21) s satsfed. Ths aks o the assumto that the roessor s ot dle as the tasks are maed oto the dataath through dvdual rado lkage lasses. Mathematally, ths s equvalet to the fat that there s a otmal kerel ma amog quasstat vetor saes. For K, thus there exsts a mmal threshold for eah arttoed rado lkage su-lass, the value of whh s gve y Equato 14). We wll rove ow that C 1 ) C, whh sgfes that task admttae ost futo for a set of multle alatos voked aross dfferet tyes of rado lkage lass assoatos overges towards the task admttae ost futo where a artular rado lkage lass s assoated wth a artular alato.

6 12 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY 2008 There s thus the rovso of hadlg alato task roesses eve f the reedee level hages the order of rado lass lkage set elemets urretly eg exeuted, as well as ay ew alato tasks that are geerated whh vokes a dfferet rado, reatg a ew assoato to a rado lkage lass. From the roertes of ay set, we have " C K..23) Thus, " " C K) C K K. 24) From equato 20), ovously, ay vetor susae, e e e K KC e, as for Parttog to susaes always reases the overall orm of the susae [8]. Thus from equato 24), we havec, whh redues toc C C, where s a salar exressg the ost futo of task admsso to all the rado lass lkage sets. Thus, we have, C 1 ).. 25) C Now, aga, we a wrte from Equato 23) " C K, whh redues to C / K)..26) Se K KC, 1/ K 1/ KC / K / KC. 27) Hee from 26), we have C 1 1/ KC ) C 1 ) C 28) From Equatos 25) ad 28) t s ow easy to see that C has a ostve overgee towardsc. From Equatos 25), 26) ad 28), the overgee s of the order of log, y exadg omally equatos 25) ad 28). Ths shows a mortat result. Whle the dyam shftg of alato task roesses aross the arttoed rado lkage lasses hels redug the task admttae ost futo, ths s deedet of the overall redtor system ehavor, ad a e roessed statly wthout ufferg, savg o ostly hardware ad atter mathg ruts. The mathematal aalyss also shows that the redtor system rut a work well uder odtos where multle alatos voke multle rados, the hysal terretato of whh s - multle alatos a e suorted o the asyhroous roessor latforms reasg the utlty of suh deves whle extedg attery lfe redug dyam ower osumto y dog away wth the OS) The mathematal aalyss forms the ass of desgg the redtor rut system ad s the key strategy ehd the hadshakg rut desg terms of tme ad ourrey. The system s ehavorally modeled osderg deedet rado ehavor ad lkage lass geerato ased o er-alato task set tye, whereas the oerato of the rut volves teral task roess trastos aross rado lkage lasses. Ths ehavor s the modeled to elmate omutatos wth artrato ad hage reedee levels of the exeuted os. The rolem of detetg whe a artular evet ours a alato task s arttoed ad lked to a artular rado lkage lass) s redued to a trval ase of aommodatg t ay artular lass set as ad whe t omes alog. There s o eed for seal detetor ruts for dog ths ostly oerato. V. EVALUATION OF THE PREDICTOR CIRCUIT SYSTEM Based o the exteded LAD mathemats [6, 7], a termedate rotool desrto ad asyhroous ehavoral model laguage s eg vestgated urretly outo wth the redtor rut system desg. We deded to use the Balsa [14] asyhroous sythess laguage ad omler terfae eause t s oe-soure ad easly ustomzale. Balsa geerates DI hadshake rut models for sythess, ad we frst looked at how to exted the omler ak-ed to geerate hadshakg models other tha DI ased o our exteded LAD arthmet. A. Modelg usg the Balsa toolset Based o the ehavoral modelg of the redtor system, t eomes ossle to exted a oet of rogrammale state level eodg delay-sestve eles where rorty of the os eg exeuted a hage at radom. Ths a hel keeg data ad delmter formato deedet of oe aother, ad hel strter otmal mas of rado-lked alato rofles to the roessor dataath. The redtor system also eeds to e modeled wth the trae results otaed durg the ode geerato ad otmzato hase assoated wth alato roflg ad omler ak-ed ostruto. Ivestgatos related to ths hase of work are urretly eg arred out. Ths desg methodology a hel to overome a dffulty asyhroous roessor ased latform desg that relates to kowg whe a sef omutato s doe for o-determst evet geerato. The rofle-derved ode has to e tegrated wth the modfed Balsa omler framework for ths urose. The ehavoral model of the redtor system s desred the Balsa laguage the modfed omler framework. The ehavoral model a e sytheszed y usual Balsa API tegrato wth stadard EDA sythess tools lke Iarus Verlog [10]. Balsa has dedated APIs for tegrato wth ths tool. The smulato was ru to omleto for our desged redtor system model ad the tme of smulato oted

7 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY tll the etre hadshakg rut grah was traversed. The left sde of the wdow ae shows the values held the uffer orts, uffer les ad ommuatg rals. The red le orresods to the hadshakg rut geerated the frst target mahe geerato. We reset the uffer smulato traes for a 2-DI rut model for hadshakg tmes of 50 µs ad 500 µs. Fg. 1. Hadshakg smulato traes of the redtor system terms of DI ad STAPL rut models 2 DI uffer, hadshakg tme 50 mroseods. Red surge uffer 2 shows the rado task alloato set almost exlusvely oued for oe tye of alato task. values of hadshakg tmes for two dual-ral ofguratos wth 8 DI uffers oeted a arallel toology wth STAPL rals. The tests were desged to kee md o-determst terrut geeratos. As rados ad alato rofles a hage retty artrarly the real-world for ortale deves, a artular rut that s already roessg formato wll eed to e terruted ad ofgured aga for roessg a dfferet set of formato. As there s o oeratg system to hael these frequet sets of terruts, the asyhroous dataath must wholly hael ths to the roessor ore. Wth reset to that ew terrut, a hadshakg rut ofgurato must ow e geerated as the target of omutato. The hadshakg rut ofgurato that s urretly reset eeds to e ated uo ased o the terrut rorty. Potetal deadloks may arse owg to artrato oteto. Wth reset to ths tme of ew target geerato, hadshakg tmes are egatve for the targets already geerated the roess. Ths also hels verfato of the redtor rut system to hael the formato rofles to the dataath removg artrato ssues. Fg.3 shows the FSM trasto of the hadshakg task grah for 8 dual-ral DI uffers wth arallel deomostos for a hadshakg tme of 100 s. Fg. 2. Hadshakg smulato traes of the redtor system terms of DI ad STAPL rut models 2 DI uffer, hadshakg tme 500 mroseods. Dual red surges uffer 2 ad the ma module shows the rado task alloato sets eg swaed for a gve alato rofle, meag that alato task os are shfted terally wth the sets. VI. EVALUATION OF THE COMPILER BACK-END DESIGN Balsa also rovdes a set of wraers that a e used to ma the target mahes geerated dretly oto ovetoal EDA sythess tools. Ths s leveraged uo to geerate the target mahes after the rado rotool desrto otmzato ad modfed LAD arthmet mlemetato the Balsa omler framework s tegrated ad ult to oe. A umer of smulatos were arred out usg the modfed LAD arthmet ased omler ak-ed usg Balsa. The exermet was arred out y settg dfferet Fg.3. FSM trasto of the hadshakg task grah for 8 DI uffer wth STAPL rals wth hadshakg tme = 100 s Ths meas that the extato to the seod target mahe geerato ofgurato was doe 100 s after the frst target mahe was geerated) VII. CONCLUSION Hgh-level desrto laguage omlato o target mahes volvg hyrd asyhroous roessor ISA s oe of the reet hoteds of fous hadset vedors owg to sueror attery lfe rosets. Ths aer shows a desg methodology wherey hgh-level desrto laguages eomassg rut ad system-level ehavor as well as rado fte state mahe FSM) exeutos a e fed to geerate hyrd asyhroous desg style hadshakg ruts. Ths aer dsusses relmary fds otaed durg the frst rototyg of hyrd asyhroous roessor-ased latforms targeted at hadset IPs. There s a oe ssue aout the target mahes hagg durg omlato the ofgurato of DI

8 14 JOURNAL OF COMPUTERS, VOL. 3, NO. 1, JANUARY 2008 ad STAPL ruts hagg ased o the tye ad umer of alatos hadled y the latform). Traslato of suh evets lke hardware terruts suh ases would eed to e traslated to the asyhroous roessor ISA a re-redted maer. Dyam target hagg the otext of a sgle rutme rogram arttog for asyhroous targets s oe aset that eeds to e ehaed the futoal exteslty of the omler ak-ed framework. The other oe ssue s the oteto dataath tmg losures due to hadshakg whe a large umer of alato tasks are volved. Ths may e dffult to mlemet usg the urret DI rut model theory that Balsa uses. Further vestgatos are eg urretly arred out ths area. REFERENCES [1] M. Reaud, P. Vvet ad F. Ro, ASPRO-16: A stadard ell DI 16-t RISC asyhroous mroroessor, ro. of 4 th. Iteratoal Symosum o Asyhroous Cruts ad Systems, ASYNC 1998, Arl 1998, [2] Mka Nystrom ad Ala J. Mart, Method ad aaratus for a asyhroous ulse log rut, Uted States Patet Alato # , Ser. # 10/693543, Ja 13, 2005 [3] USC Asyhroous VLSI Desg, htt://ugfrau.us.edu/ew/researh/urret/asy1 [4] Rat Maohar, Wdth-adatve data word arhtetures, ro. of Advaed Researh VLSI 2001, ARVLSI 2001, Marh 2001, [5] V. Ekaayake, Clto Kelly IV ad R. Maohar, A ultra-low ower roessor for sesor etworks, ro. of 11 th. Iteratoal Coferee o Arhtetural Suort for Programmg Laguages ad Oeratg Systems, ACM ASPLOS, Arl 2004, [6] Daraya Guha ad Thamlla Srkatha, Reofgurale Frame Parser Desg for Mult-Rado Suort o Asyhroous Mroroessor Cores, ro. of IEEE Iteratoal Coferee o Comutg: Theory ad Alatos, ICCTA 2007, Platum Julee of the Ida Statstal Isttute, Marh 2007, [7] Daraya Guha ad Thamlla Srkatha, Mult- Rado suort o Asyhroous Proessor Cores: A Desg Methodology aroah for Cogtve Rados, ro. of IEEE Iteratoal Coferee o Portale Iformato Deves, PORTABLE 2007, May 2007,. 1-4 [8] Dael Smso, Lear reresetatos of artally ordered sets ad vetor sae ategores, Gordo ad Breah See Pulshers, 1992 [9] The Balsa Asyhroous Sythess System, Uversty of Mahester Advaed Proessor Tehologes Grou, htt://traet.s.ma.a.uk/at/roets/tools/alsa [10] Iarus Verlog, htt:// Daraya Guha reeved hs B.Eg. Frst Class Hoors) degree Eletros ad Teleommuatos Egeerg from Jadavur Uversty, Calutta, Ida, 2000 ad hs M.Eg degree Eletral Egeerg from Corell Uversty, Ithaa, New York, He urretly holds a teured osto of Researh Assoate wth the Ceter for Hgh Performae Emedded Systems, Nayag Tehologal Uversty, Sgaore. Pror to ths aotmet, he had worked wth Saske, Aglet Tehologes ad Samsug. He has ulshed more tha 15 aers the areas of emedded systems desg methodologes ad data ommuatos. He s also a atve otrutor to teret egeerg stadards ad has o-authored fve teret drafts o ath omutato that were soured to eome RFCs the IETF PCE WG. Mr. Guha wo the Brtsh Cheveg Sholarsh 2003 ad a NSF studet aer award Dr. Thamlla Srkatha reeved hs B.S. degree Hoors) Comuter ad Cotrol Systems ad hs Ph.D. System Modelg ad Iformato Systems Egeerg from Covetry Uversty, Uted Kgdom, 1980 ad 1986 resetvely. He s the Dretor of Ceter for Hgh Performae Emedded Systems ad teured Professor of Comuter Egeerg, Nayag Tehologal Uversty, Sgaore. He has ulshed more tha 220 aers ad holds three veto dslosures. Hs researh terests lude alato-sef arhtetures for emedded systems ad desg methodologes for hgh erformae emedded systems. Dr. Srkatha s a Cororate Memer of the Isttuto of Eletral Egeers MIEE) ad Chartered Egeer CEg) se He s also a Seor Memer of the Isttute of Eletral ad Eletros Egeers SMIEEE) se Dr. Srkatha was awarded the Pul Admstrato Medal Broze) o 2006 Sgaore Natoal Day for outstadg otrutos to eduato Sgaore.

Single machine stochastic appointment sequencing and scheduling

Single machine stochastic appointment sequencing and scheduling Sgle mahe stohast aotmet sequeg ad shedulg We develo algorthms for a sgle mahe stohast aotmet sequeg ad shedulg roblem th atg tme, dle tme, ad overtme osts. Ths s a bas stohast shedulg roblem that has

More information

MDM 4U PRACTICE EXAMINATION

MDM 4U PRACTICE EXAMINATION MDM 4U RCTICE EXMINTION Ths s a ractce eam. It does ot cover all the materal ths course ad should ot be the oly revew that you do rearato for your fal eam. Your eam may cota questos that do ot aear o ths

More information

A Fast Algorithm for Computing the Deceptive Degree of an Objective Function

A Fast Algorithm for Computing the Deceptive Degree of an Objective Function IJCSNS Iteratoal Joural of Computer See ad Networ Seurty, VOL6 No3B, Marh 6 A Fast Algorthm for Computg the Deeptve Degree of a Objetve Futo LI Yu-qag Eletro Tehque Isttute, Zhegzhou Iformato Egeerg Uversty,

More information

Average Price Ratios

Average Price Ratios Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or

More information

Checking Out the Doght Stadard Odors in Polygamy

Checking Out the Doght Stadard Odors in Polygamy Cosstey Test o Mass Calbrato of Set of Weghts Class ad Lowers Lus Oar Beerra, Igao Herádez, Jorge Nava, Fél Pezet Natoal Ceter of Metrology (CNAM) Querétaro, Meo Abstrat: O weghts albrato oe by oe there

More information

Approximation Algorithms for Scheduling with Rejection on Two Unrelated Parallel Machines

Approximation Algorithms for Scheduling with Rejection on Two Unrelated Parallel Machines (ICS) Iteratoal oural of dvaced Comuter Scece ad lcatos Vol 6 No 05 romato lgorthms for Schedulg wth eecto o wo Urelated Parallel aches Feg Xahao Zhag Zega Ca College of Scece y Uversty y Shadog Cha 76005

More information

Fuzzy Risk Evaluation Method for Information Technology Service

Fuzzy Risk Evaluation Method for Information Technology Service Fuzzy Rsk Evaluato Method for Iformato Tehology Serve Outsourg Qasheg Zhag Yrog Huag Fuzzy Rsk Evaluato Method for Iformato Tehology Serve Outsourg 1 Qasheg Zhag 2 Yrog Huag 1 Shool of Iformats Guagdog

More information

A Hierarchical Fuzzy Linear Regression Model for Forecasting Agriculture Energy Demand: A Case Study of Iran

A Hierarchical Fuzzy Linear Regression Model for Forecasting Agriculture Energy Demand: A Case Study of Iran 3rd Iteratoal Coferee o Iformato ad Faal Egeerg IPEDR vol. ( ( IACSIT Press, Sgapore A Herarhal Fuzz Lear Regresso Model for Foreastg Agrulture Eerg Demad: A Case Stud of Ira A. Kazem, H. Shakour.G, M.B.

More information

THE EQUILIBRIUM MODELS IN OLIGOPOLY ELECTRICITY MARKET

THE EQUILIBRIUM MODELS IN OLIGOPOLY ELECTRICITY MARKET Iteratoal Coferee The Euroea Eletrty Market EEM-4 etember -, 4, Lodz, Polad Proeedg Volume,. 35-4 THE EQUILIBRIUM MODEL IN OLIGOPOLY ELECTRICITY MARKET Agezka Wyłomańka Wrolaw Uverty of Tehology Wrolaw

More information

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira sedgh@eetd.ktu.ac.r,

More information

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time.

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time. Computatoal Geometry Chapter 6 Pot Locato 1 Problem Defto Preprocess a plaar map S. Gve a query pot p, report the face of S cotag p. S Goal: O()-sze data structure that eables O(log ) query tme. C p E

More information

A Comparison of the Performance of Two-Tier Cellular Networks Based on Queuing Handoff Calls

A Comparison of the Performance of Two-Tier Cellular Networks Based on Queuing Handoff Calls Iteratoal Joural of Appled Matemats ad Computer Sees 2;2 www.waset.org Sprg 2006 A Comparso of te erformae of Two-Ter Cellular Networks Based o Queug Hadoff Calls Tara Sal ad Kemal Fdaboylu Abstrat Two-ter

More information

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected

More information

Universal Prediction Applied to Stylistic Music Generation Gיrard Assayag (Ircam), Shlomo Dubnov (Ben Gurion Univ.)

Universal Prediction Applied to Stylistic Music Generation Gיrard Assayag (Ircam), Shlomo Dubnov (Ben Gurion Univ.) Uversal Predto Appled to Stylst Mus Geerato Gיrard Assayag (Iram), Shlomo Dubov (Be Guro Uv.) Abstrat Capturg a style of a partular pee or a omposer s ot a easy task. Several attempts to use mahe learg

More information

Numerical Methods with MS Excel

Numerical Methods with MS Excel TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how

More information

CSSE463: Image Recognition Day 27

CSSE463: Image Recognition Day 27 CSSE463: Image Recogto Da 27 Ths week Toda: Alcatos of PCA Suda ght: roject las ad relm work due Questos? Prcal Comoets Aalss weght grth c ( )( ) ( )( ( )( ) ) heght sze Gve a set of samles, fd the drecto(s)

More information

Green Master based on MapReduce Cluster

Green Master based on MapReduce Cluster Gree Master based o MapReduce Cluster Mg-Zh Wu, Yu-Chag L, We-Tsog Lee, Yu-Su L, Fog-Hao Lu Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of

More information

Improving website performance for search engine optimization by using a new hybrid MCDM model

Improving website performance for search engine optimization by using a new hybrid MCDM model Improvg webste performae for searh ege optmzato by usg a ew hybrd MDM model Ye-hag he Isttute of ha ad Asa-Paf Studes, Natoal Su Yat-se Uversty, awa, R.O.. tayler530259@gmal.om Yu-Sheg Lu Departmet of

More information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information JOURNAL OF SOFWARE, VOL 5, NO 3, MARCH 00 75 Models for Selectg a ERP System wth Itutostc rapezodal Fuzzy Iformato Guwu We, Ru L Departmet of Ecoomcs ad Maagemet, Chogqg Uversty of Arts ad Sceces, Yogchua,

More information

Hi-Tech Authentication for Palette Images Using Digital Signature and Data Hiding

Hi-Tech Authentication for Palette Images Using Digital Signature and Data Hiding The Iteratoal Arab Joural of Iformato Tehology, Vol. 8, No., Aprl 0 7 H-Teh Authetato for Palette Images Usg Dgtal Sgature ad Data Hdg Aroka Jasra, Regasvaguruatha Rajesh, Ramasamy Balasubramaa, ad Perumal

More information

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li Iteratoal Joural of Scece Vol No7 05 ISSN: 83-4890 Proecto model for Computer Network Securty Evaluato wth terval-valued tutostc fuzzy formato Qgxag L School of Software Egeerg Chogqg Uversty of rts ad

More information

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ  1 STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ

More information

The Time Value of Money

The Time Value of Money The Tme Value of Moey 1 Iversemet Optos Year: 1624 Property Traded: Mahatta Islad Prce : $24.00, FV of $24 @ 6%: FV = $24 (1+0.06) 388 = $158.08 bllo Opto 1 0 1 2 3 4 5 t ($519.37) 0 0 0 0 $1,000 Opto

More information

The Digital Signature Scheme MQQ-SIG

The Digital Signature Scheme MQQ-SIG The Dgtal Sgature Scheme MQQ-SIG Itellectual Property Statemet ad Techcal Descrpto Frst publshed: 10 October 2010, Last update: 20 December 2010 Dalo Glgorosk 1 ad Rue Stesmo Ødegård 2 ad Rue Erled Jese

More information

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity Computer Aded Geometrc Desg 19 (2002 365 377 wwwelsevercom/locate/comad Optmal mult-degree reducto of Bézer curves wth costrats of edpots cotuty Guo-Dog Che, Guo-J Wag State Key Laboratory of CAD&CG, Isttute

More information

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0 Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may

More information

Measuring the Quality of Credit Scoring Models

Measuring the Quality of Credit Scoring Models Measur the Qualty of Credt cor Models Mart Řezáč Dept. of Matheatcs ad tatstcs, Faculty of cece, Masaryk Uversty CCC XI, Edurh Auust 009 Cotet. Itroducto 3. Good/ad clet defto 4 3. Measur the qualty 6

More information

On Error Detection with Block Codes

On Error Detection with Block Codes BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 9, No 3 Sofa 2009 O Error Detecto wth Block Codes Rostza Doduekova Chalmers Uversty of Techology ad the Uversty of Gotheburg,

More information

Real-Time Scheduling Models: an Experimental Approach

Real-Time Scheduling Models: an Experimental Approach Real-Tme Schedulg Models: a Expermetal Approach (Techcal Report - Nov. 2000) Atóo J. Pessoa de Magalhães a.p.magalhaes@fe.up.pt Fax: 22 207 4247 SAI DEMEGI Faculdade de Egehara da Uversdade do Porto -

More information

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has

More information

Chapter 7 Dynamics. 7.1 Newton-Euler Formulation of Equations of Motion

Chapter 7 Dynamics. 7.1 Newton-Euler Formulation of Equations of Motion Itroduto to Robots,. arry Asada Chapter 7 Dyams I ths hapter, we aalyze the dyam behavor of robot mehasms. he dyam behavor s desrbed terms of the tme rate of hage of the robot ofgurato relato to the ot

More information

RUSSIAN ROULETTE AND PARTICLE SPLITTING

RUSSIAN ROULETTE AND PARTICLE SPLITTING RUSSAN ROULETTE AND PARTCLE SPLTTNG M. Ragheb 3/7/203 NTRODUCTON To stuatos are ecoutered partcle trasport smulatos:. a multplyg medum, a partcle such as a eutro a cosmc ray partcle or a photo may geerate

More information

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation Securty Aalyss of RAPP: A RFID Authetcato Protocol based o Permutato Wag Shao-hu,,, Ha Zhje,, Lu Sujua,, Che Da-we, {College of Computer, Najg Uversty of Posts ad Telecommucatos, Najg 004, Cha Jagsu Hgh

More information

Models of migration. Frans Willekens. Colorado Conference on the Estimation of Migration 24 26 September 2004

Models of migration. Frans Willekens. Colorado Conference on the Estimation of Migration 24 26 September 2004 Models of mgrato Fras Wllekes Colorado Coferece o the Estmato of Mgrato 4 6 Setember 004 Itroducto Mgrato : chage of resdece (relocato Mgrato s stuated tme ad sace Cocetual ssues Sace: admstratve boudares

More information

Spatial Keyframing for Performance-driven Animation

Spatial Keyframing for Performance-driven Animation Eurographs/ACSIGGRAPH Symposum o Computer Amato (25) K. Ajyo, P. Faloutsos (Edtors) Spatal Keyframg for Performae-drve Amato T. Igarash,3, T. osovh 2, ad J. F. Hughes 2 The Uversty of Tokyo 2 Brow Uversty

More information

An Effectiveness of Integrated Portfolio in Bancassurance

An Effectiveness of Integrated Portfolio in Bancassurance A Effectveess of Itegrated Portfolo Bacassurace Taea Karya Research Ceter for Facal Egeerg Isttute of Ecoomc Research Kyoto versty Sayouu Kyoto 606-850 Japa arya@eryoto-uacp Itroducto As s well ow the

More information

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there

More information

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50

More information

Classic Problems at a Glance using the TVM Solver

Classic Problems at a Glance using the TVM Solver C H A P T E R 2 Classc Problems at a Glace usg the TVM Solver The table below llustrates the most commo types of classc face problems. The formulas are gve for each calculato. A bref troducto to usg the

More information

Automated Event Registration System in Corporation

Automated Event Registration System in Corporation teratoal Joural of Advaces Computer Scece ad Techology JACST), Vol., No., Pages : 0-0 0) Specal ssue of CACST 0 - Held durg 09-0 May, 0 Malaysa Automated Evet Regstrato System Corporato Zafer Al-Makhadmee

More information

Compressive Sensing over Strongly Connected Digraph and Its Application in Traffic Monitoring

Compressive Sensing over Strongly Connected Digraph and Its Application in Traffic Monitoring Compressve Sesg over Strogly Coected Dgraph ad Its Applcato Traffc Motorg Xao Q, Yogca Wag, Yuexua Wag, Lwe Xu Isttute for Iterdscplary Iformato Sceces, Tsghua Uversty, Bejg, Cha {qxao3, kyo.c}@gmal.com,

More information

A Parallel Transmission Remote Backup System

A Parallel Transmission Remote Backup System 2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College

More information

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS L et al.: A Dstrbuted Reputato Broker Framework for Web Servce Applcatos A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS Kwe-Jay L Departmet of Electrcal Egeerg ad Computer Scece

More information

of the relationship between time and the value of money.

of the relationship between time and the value of money. TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp

More information

An Intelligent E-commerce Recommender System Based on Web Mining

An Intelligent E-commerce Recommender System Based on Web Mining Iteratioal Joural of Busiess ad Maagemet A Itelliget E-ommere Reommeder System Based o We Miig Zimig Zeg Shool of Iformatio Maagemet, Wuha Uiversity Wuha 43007, Chia E-mail: zmzeg1977@yahoo.om. The researh

More information

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable

More information

Online Appendix: Measured Aggregate Gains from International Trade

Online Appendix: Measured Aggregate Gains from International Trade Ole Appedx: Measured Aggregate Gas from Iteratoal Trade Arel Burste UCLA ad NBER Javer Cravo Uversty of Mchga March 3, 2014 I ths ole appedx we derve addtoal results dscussed the paper. I the frst secto,

More information

Geometric Motion Planning and Formation Optimization for a Fleet of Nonholonomic Wheeled Mobile Robots

Geometric Motion Planning and Formation Optimization for a Fleet of Nonholonomic Wheeled Mobile Robots Proceedgs of the 4 IEEE Iteratoal Coferece o Robotcs & Automato New Orleas, LA Arl 4 Geometrc oto Plag ad Formato Otmzato for a Fleet of Noholoomc Wheeled oble Robots Rajakumar Bhatt echacal & Aerosace

More information

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET İstabul Tcaret Üverstes Fe Blmler Dergs Yıl: 5 Sayı:0 Güz 006/ s. - OPTIMAL KNOWLEDGE FLOW ON THE INTERNET Bura ORDİN *, Urfat NURİYEV ** ABSTRACT The flow roblem ad the mmum sag tree roblem are both fudametal

More information

10.5 Future Value and Present Value of a General Annuity Due

10.5 Future Value and Present Value of a General Annuity Due Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the

More information

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral

More information

RESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL CLOUD APPLICATIONS

RESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL CLOUD APPLICATIONS Joural of Theoretcal ad Appled Iformato Techology 3 st October 22. Vol. 44 No.2 25-22 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 RESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL

More information

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree , pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal

More information

How do bookmakers (or FdJ 1 ) ALWAYS manage to win?

How do bookmakers (or FdJ 1 ) ALWAYS manage to win? How do bookakers (or FdJ ALWAYS aage to w? Itroducto otatos & varables Bookaker's beeft eected value 4 4 Bookaker's strateges5 4 The hoest bookaker 6 4 "real lfe" bookaker 6 4 La FdJ 8 5 How ca we estate

More information

Integrating Production Scheduling and Maintenance: Practical Implications

Integrating Production Scheduling and Maintenance: Practical Implications Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk

More information

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R = Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are

More information

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. Proceedgs of the 21 Wter Smulato Coferece B. Johasso, S. Ja, J. Motoya-Torres, J. Huga, ad E. Yücesa, eds. EMPIRICAL METHODS OR TWO-ECHELON INVENTORY MANAGEMENT WITH SERVICE LEVEL CONSTRAINTS BASED ON

More information

Discrete-Event Simulation of Network Systems Using Distributed Object Computing

Discrete-Event Simulation of Network Systems Using Distributed Object Computing Dscrete-Evet Smulato of Network Systems Usg Dstrbuted Object Computg Welog Hu Arzoa Ceter for Itegratve M&S Computer Scece & Egeerg Dept. Fulto School of Egeerg Arzoa State Uversty, Tempe, Arzoa, 85281-8809

More information

CHAPTER 2. Time Value of Money 6-1

CHAPTER 2. Time Value of Money 6-1 CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show

More information

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1 akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of

More information

How To Make A Supply Chain System Work

How To Make A Supply Chain System Work Iteratoal Joural of Iformato Techology ad Kowledge Maagemet July-December 200, Volume 2, No. 2, pp. 3-35 LATERAL TRANSHIPMENT-A TECHNIQUE FOR INVENTORY CONTROL IN MULTI RETAILER SUPPLY CHAIN SYSTEM Dharamvr

More information

n. We know that the sum of squares of p independent standard normal variables has a chi square distribution with p degrees of freedom.

n. We know that the sum of squares of p independent standard normal variables has a chi square distribution with p degrees of freedom. UMEÅ UNIVERSITET Matematsk-statstska sttutoe Multvarat dataaalys för tekologer MSTB0 PA TENTAMEN 004-0-9 LÖSNINGSFÖRSLAG TILL TENTAMEN I MATEMATISK STATISTIK Multvarat dataaalys för tekologer B, 5 poäg.

More information

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are : Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of

More information

Study on prediction of network security situation based on fuzzy neutral network

Study on prediction of network security situation based on fuzzy neutral network Avalable ole www.ocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(6):00-06 Research Artcle ISS : 0975-7384 CODE(USA) : JCPRC5 Study o predcto of etwork securty stuato based o fuzzy eutral etwork

More information

Opinion Extraction, Summarization and Tracking in News and Blog Corpora

Opinion Extraction, Summarization and Tracking in News and Blog Corpora Opo Extrato, Suarzato ad Trakg ews ad Blog Corpora Lu-We Ku, Yu-Tg Lag ad Hs-Hs Che Departet of Coputer See ad Iforato Egeerg atoal Tawa Uversty Tape, Tawa {lwku, eaga}@lg.se.tu.edu.tw; hhhe@se.tu.edu.tw

More information

RQM: A new rate-based active queue management algorithm

RQM: A new rate-based active queue management algorithm : A ew rate-based actve queue maagemet algorthm Jeff Edmods, Suprakash Datta, Patrck Dymod, Kashf Al Computer Scece ad Egeerg Departmet, York Uversty, Toroto, Caada Abstract I ths paper, we propose a ew

More information

Common p-belief: The General Case

Common p-belief: The General Case GAMES AND ECONOMIC BEHAVIOR 8, 738 997 ARTICLE NO. GA97053 Commo p-belef: The Geeral Case Atsush Kaj* ad Stephe Morrs Departmet of Ecoomcs, Uersty of Pesylaa Receved February, 995 We develop belef operators

More information

Chapter Eight. f : R R

Chapter Eight. f : R R Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,

More information

1. The Time Value of Money

1. The Time Value of Money Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg

More information

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis 6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces

More information

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component Beta A Statstcal Aalyss of a Stock s Volatlty Courtey Wahlstrom Iowa State Uversty, Master of School Mathematcs Creatve Compoet Fall 008 Amy Froelch, Major Professor Heather Bolles, Commttee Member Travs

More information

APPENDIX III THE ENVELOPE PROPERTY

APPENDIX III THE ENVELOPE PROPERTY Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful

More information

Relaxation Methods for Iterative Solution to Linear Systems of Equations

Relaxation Methods for Iterative Solution to Linear Systems of Equations Relaxato Methods for Iteratve Soluto to Lear Systems of Equatos Gerald Recktewald Portlad State Uversty Mechacal Egeerg Departmet gerry@me.pdx.edu Prmary Topcs Basc Cocepts Statoary Methods a.k.a. Relaxato

More information

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,

More information

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable

More information

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,

More information

STRATEGIC SUPPLY FUNCTION COMPETITION WITH PRIVATE INFORMATION. Xavier Vives. October 2009 COWLES FOUNDATION DISCUSSION PAPER NO.

STRATEGIC SUPPLY FUNCTION COMPETITION WITH PRIVATE INFORMATION. Xavier Vives. October 2009 COWLES FOUNDATION DISCUSSION PAPER NO. STRATEGIC SUPPLY FUNCTION COMPETITION WITH PRIVATE INFORMATION By Xaver Vves Otober 009 COWLES FOUNDATION DISCUSSION PAPER NO. 1736 COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY Box 0881

More information

Bayesian Network Representation

Bayesian Network Representation Readgs: K&F 3., 3.2, 3.3, 3.4. Bayesa Network Represetato Lecture 2 Mar 30, 20 CSE 55, Statstcal Methods, Sprg 20 Istructor: Su-I Lee Uversty of Washgto, Seattle Last tme & today Last tme Probablty theory

More information

Web Services Wind Tunnel: On Performance Testing Large-scale Stateful Web Services

Web Services Wind Tunnel: On Performance Testing Large-scale Stateful Web Services Web Servces Wd Tuel: O Performace Testg Large-scale Stateful Web Servces Marcelo De Barros, Jg Shau, Che Shag, Keto Gdewall, Hu Sh, Joe Forsma Mcrosoft Cororato {marcelod,shau,cshag,ketog,hush,osehfo}@mcrosoft.com

More information

STATIC ANALYSIS OF TENSEGRITY STRUCTURES

STATIC ANALYSIS OF TENSEGRITY STRUCTURES SI NYSIS O ENSEGIY SUUES JUIO ES OE HESIS PESENED O HE GDUE SHOO O HE UNIVESIY O OID IN PI UIEN O HE EQUIEENS O HE DEGEE O SE O SIENE UNIVESIY O OID o m mother for her fte geerost. KNOWEDGENS I wat to

More information

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts Optmal replacemet ad overhaul decsos wth mperfect mateace ad warraty cotracts R. Pascual Departmet of Mechacal Egeerg, Uversdad de Chle, Caslla 2777, Satago, Chle Phoe: +56-2-6784591 Fax:+56-2-689657 rpascual@g.uchle.cl

More information

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011 Cyber Jourals: Multdscplary Jourals cece ad Techology, Joural of elected Areas Telecommucatos (JAT), Jauary dto, 2011 A ovel rtual etwork Mappg Algorthm for Cost Mmzg ZHAG hu-l, QIU Xue-sog tate Key Laboratory

More information

STATISTICAL ANALYSIS OF WIND SPEED DATA

STATISTICAL ANALYSIS OF WIND SPEED DATA Esşehr Osmagaz Üerstes Müh.Mm.Fa.Dergs C. XVIII, S.2, 2005 Eg.&Arh.Fa. Esşehr Osmagaz Uersty, Vol. XVIII, No: 2, 2005 STATISTICAL ANALYSIS OF WIND SPEED DATA Veysel YILMAZ, Haydar ARAS 2, H.Eray ÇELİK

More information

A particle swarm optimization to vehicle routing problem with fuzzy demands

A particle swarm optimization to vehicle routing problem with fuzzy demands A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg, Ye-me Qa A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg 1,Ye-me Qa 1 School of computer ad formato

More information

Three Dimensional Interpolation of Video Signals

Three Dimensional Interpolation of Video Signals Three Dmesoal Iterpolato of Vdeo Sgals Elham Shahfard March 0 th 006 Outle A Bref reve of prevous tals Dgtal Iterpolato Bascs Upsamplg D Flter Desg Issues Ifte Impulse Respose Fte Impulse Respose Desged

More information

Master Thesis Mathematical Modeling and Simulation On Fuzzy linear programming problems solved with Fuzzy decisive set method

Master Thesis Mathematical Modeling and Simulation On Fuzzy linear programming problems solved with Fuzzy decisive set method 008:05 Mster Thess Mthemt Modeg d Smuto O Fuzzy er progrmmg proems soved wth Fuzzy desve set method Author shd Mehmood Thess for the degree Mster of Mthemt Modeg d Smuto 5 redt pots 5 ECTS redts 08 009

More information

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad sheha@elec.caterbury.ac.z

More information

Network dimensioning for elastic traffic based on flow-level QoS

Network dimensioning for elastic traffic based on flow-level QoS Network dmesog for elastc traffc based o flow-level QoS 1(10) Network dmesog for elastc traffc based o flow-level QoS Pas Lassla ad Jorma Vrtamo Networkg Laboratory Helsk Uversty of Techology Itroducto

More information

Efficient Traceback of DoS Attacks using Small Worlds in MANET

Efficient Traceback of DoS Attacks using Small Worlds in MANET Effcet Traceback of DoS Attacks usg Small Worlds MANET Yog Km, Vshal Sakhla, Ahmed Helmy Departmet. of Electrcal Egeerg, Uversty of Souther Calfora, U.S.A {yogkm, sakhla, helmy}@ceg.usc.edu Abstract Moble

More information

Fuzzy Task Assignment Model of Web Services Supplier in Collaborative Development Environment

Fuzzy Task Assignment Model of Web Services Supplier in Collaborative Development Environment , pp.199-210 http://dx.do.org/10.14257/uesst.2015.8.6.19 Fuzzy Task Assget Model of Web Servces Suppler Collaboratve Developet Evroet Su Ja 1,2, Peg Xu-ya 1, *, Xu Yg 1,3, Wag Pe-e 2 ad Ma Na- 4,2 1. College

More information

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK Fractal-Structured Karatsuba`s Algorthm for Bary Feld Multplcato: FK *The authors are worg at the Isttute of Mathematcs The Academy of Sceces of DPR Korea. **Address : U Jog dstrct Kwahadog Number Pyogyag

More information

The Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk

The Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk The Aalyss of Developmet of Isurace Cotract Premums of Geeral Lablty Isurace the Busess Isurace Rsk the Frame of the Czech Isurace Market 1998 011 Scetfc Coferece Jue, 10. - 14. 013 Pavla Kubová Departmet

More information

The impact of service-oriented architecture on the scheduling algorithm in cloud computing

The impact of service-oriented architecture on the scheduling algorithm in cloud computing Iteratoal Research Joural of Appled ad Basc Sceces 2015 Avalable ole at www.rjabs.com ISSN 2251-838X / Vol, 9 (3): 387-392 Scece Explorer Publcatos The mpact of servce-oreted archtecture o the schedulg

More information

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa

More information

Performance Attribution. Methodology Overview

Performance Attribution. Methodology Overview erformace Attrbuto Methodology Overvew Faba SUAREZ March 2004 erformace Attrbuto Methodology 1.1 Itroducto erformace Attrbuto s a set of techques that performace aalysts use to expla why a portfolo's performace

More information

Vibration and Speedy Transportation

Vibration and Speedy Transportation Research Paper EAEF (3) : 8-5, 9 Path Plag of Tomato Cluster Harvestg Robot for Realzg Low Vbrato ad Speedy Trasportato Naosh KONDO *, Koch TANIHARA *, Tomowo SHIIGI *, Hrosh SHIMIZU *, Mtsutaka KURITA

More information

Mathematics of Finance

Mathematics of Finance CATE Mathematcs of ace.. TODUCTO ths chapter we wll dscuss mathematcal methods ad formulae whch are helpful busess ad persoal face. Oe of the fudametal cocepts the mathematcs of face s the tme value of

More information

Application of Grey Relational Analysis in Computer Communication

Application of Grey Relational Analysis in Computer Communication Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato Jgcha J Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato *1 Jgcha J *1, Frst ad Correspodg Author

More information

Settlement Prediction by Spatial-temporal Random Process

Settlement Prediction by Spatial-temporal Random Process Safety, Relablty ad Rs of Structures, Ifrastructures ad Egeerg Systems Furuta, Fragopol & Shozua (eds Taylor & Fracs Group, Lodo, ISBN 978---77- Settlemet Predcto by Spatal-temporal Radom Process P. Rugbaapha

More information

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE ANNEX 77 FINANCE MANAGEMENT (Workg materal) Chef Actuary Prof. Gada Pettere BTA INSURANCE COMPANY SE 1 FUNDAMENTALS of INVESTMENT I THEORY OF INTEREST RATES 1.1 ACCUMULATION Iterest may be regarded as

More information