PASAP: Power Aware Structured ASIC Placement

Size: px
Start display at page:

Download "PASAP: Power Aware Structured ASIC Placement"

Transcription

1 PASAP: Powr Awr Strutur ASIC Plmnt Ashutosh Chkrorty ECE Dprtmnt Univrsity o Txs t Austin Austin, Txs, USA shutosh@r.utxs.u Dvi Z. Pn ECE Dprtmnt Univrsity o Txs t Austin Austin, Txs, USA pn@.utxs.u ABSTRACT Strutur ASICs provi n xiting mil groun twn FPGA n ASIC sign mthoologis. Compr to ASIC, strutur ASIC s signs rquir lowr non rurring nginring (NRE) osts n turn-roun-tim ut sur rom highr powr onsumption n lowr prormn. Powr rution or strutur ASICs uss xtnsiv lok n supply powr-own o unus iruitry n us o low powr vis. Howvr, u to th limit grnulrity o powr-own, physil sign (spilly plmnt) shoul prorm to mximiz th omponnts tht n powr own. In this ppr, w prsnt th irst plmnt lgorithm to spiilly trgt this prolm. Our tool, PASAP (Powr Awr Strutur ASIC Plmnt), minimizs th lok n lkg powr y mximizing th rtion o th strutur ASIC tht n powr own or isonnt rom lok tr. On st o lrg nhmrk signs, PASAP rus lok n lkg powr y 32% n 17% rsptivly ompr to prior strutur ASIC plmnt tool RgPl [1] inurring 17% pnlty in wirlngth n 30% longr runtim. Ctgoris n Sujt Dsriptors B.7.2 [Hrwr, Intgrt Ciruit]: Dsign Ais Gnrl Trms Algorithms, Dsign Kywors low powr, plmnt, rgulr ris, strutur ASICs 1. INTRODUCTION Skyrokting osts n inrsing vriility ssoit with n ASIC sign low n unptl powr n ly pnlty ssoit with FPGA sign low hv or smionutor ompnis to look or ltrntivs. On vil ltrntiv tht hs mrg ovr tim is th us o strutur ASICs. Strutur ASICs provi n xiting mil-groun twn high prormn o ASIC signs n short tim-to-mrkt FPGA Prmission to mk igitl or hr opis o ll or prt o this work or prsonl or lssroom us is grnt without provi tht opis r not m or istriut or proit or ommril vntg n tht opis r this noti n th ull ittion on th irst pg. To opy othrwis, to rpulish, to post on srvrs or to ristriut to lists, rquirs prior spii prmission n/or. ISLPED 10, August 18 20, 2010, Austin, Txs, USA. Copyright 2010 ACM /10/08...$ signs. Thy xploit th t tht not ll msk-lyrs provi qul vlu or th ustomrs n ths lyrs n pr-rit mortizing thir ost ovr multipl signs [2]. Strutur ASIC low is muh simplr thn tht or tritionl ASICs us mjority o p sumiron issus suh s signl intgrity, powr gri optimiztion, low skw lok tr istriution r lry tkn r o y th strutur ASIC vnors. Highr powr onsumption ompr to th ASIC pproh n prov to th Ahills hl o strutur ASIC mthoology. To ru th powr pnlty, thr hv n mny innovtions in thir rhittur inluing us o vi progrmming (inst o SRAMs whih rin lkg powr), low lkg tripl oxi vis, n powr-own o unus omponnts. From th EDA prsptiv, th powr svings n inrs i th sign tools n xploit ths powr optimiztion mthos. On suh stp is to nhn plmnt lgorithms to mximiz th unus omponnts so tht thy n powr own. Distriution o lls s i y plmnt trmins whih rs o th strutur ASICs must rmin powr on. Du to limit grnulrity o powr own vill, mny non untioning vis my or to rmin powr up u to nighoring untioning vis, ling to wst lkg powr. In ition, plmnt lso trmins th xtnt o th lok ntwork tht must swith t h lok yl. Typilly, lls longing to only on lok group n pl los to h othr, thror wrong istriution o lls n signiintly urn muh mor powr y rquiring lrgr lok ntwork to rmin tiv. In this ppr, w tkl powr wr plmnt on strutur ASIC pltorms or th irst tim n propos mthos to ru th lkg n lok powr. Th rst o this ppr is orgniz s ollows: W provi kgroun o strutur ASIC rhittur n plmnt in Stion 2. Stion 3 tils th lkg n lok powr mol us to vlut th plmnt solution. Powr wr strutur ASIC plr (PASAP) is prsnt in Stion 4. Th xprimntl stup is sri in Stion 5. Powr rution rsults r prsnt in Stion 6. Stion 7 onlus our ppr. 2. BACKGROUND 2.1 Strutur ASIC Arhittur Lik FPGAs, strutur ASICs onsist o rgulr 2-D rptition o si uiling lok ll til. Dpning on th siz o th sign to implmnt on strutur ASIC, th numr o rptition o th tils in th horizontl n vrtil irtion n moii. Th physil strutur hiv y rptition o th til rtin numr o tims, will rrr to s pltorm. Sin til is th si uiling lok o strutur ASIC, w sri its rhittur nxt. 395

2 Eh til is rtngulr rgion in whih th vis r prrit. Thr n mny irnt units rit in til suh s logi lls, lip lops, multiplxrs, rs t. In this work, w will primrily trgt th rhittur o til s rls y ling strutur ASIC ompny ASIC [3] s prt o thir worlwi plmnt ontst. Thr r our irnt typs o lls rit in h til: logi lls, lip lops units, rgistr ils n RAMs. W rr to ths lls s LOGC, DFF, REG, n RAM rsptivly in th rst o th ppr. Th rltiv siz o ths lls r 1x1, 1x1, 8x32, n 16x64 thus thir r is in th rtio 1:1:256:1024 rsptivly. Expt LOGC, ll othr ll typs r squntil in ntur. Th lotions whr ths lls r pr-rit in th til r s shown in Figur 1. LOGC n DFF lls r rit in olumns o hight 64 h. Thr r 36 n 24 olumns (not ll shown in Figur 1) o LOGC n DFF lls rsptivly in h til. At th ntr o th til, on RAM is rit n hl o th olumns o LOGC ndff h ppr on oth si o th RAM ll. On th right n o th til, 4 REG r rit in 2x2 rry ormtion. In summry, h til hs 2304 LOGC, 1536 DFF, 4 REG n 1 RAM lls. Clok routing onstrints itt tht not mor thn w loks n istriut in til (though th pltorm n hv mny mor uniqu loks). Thror, th squntil lls insi h til shoul not rquir mor thn givn numr o uniqu loks. Til LCELL BRAM DFF REG Intr-til sp Figur 1: Strutur ASIC pltorm. 2.2 Strutur ASIC Plmnt Plmnt on strutur ASIC tks s input ) n RTL xprss in trms o LOGC, DFF, REG, n RAM lls, ) th rhittur o th strutur ASIC pltorm, ) Gomtry inormtion out th til, n ) Clok onstrints t th pltorm n t th til lvl; n mps h ll to pr-rit lotion on th pltorm suh tht sit omptiility s wll s lok onstrints r stisi. Th ojtiv o th plmnt n to minimiz wirlngth or ly o th iruit whil mting ths onstrints. Prvious Work: Rnt plmnt ontst sponsor y ASIC [3] ostr rsrh in th il o plmnt or strutur ASICs. Hr w sri th grn priz winning ntry RgPl [1]. Du to its vilility (opn sour) n high qulity, w us RgPl s our plmnt rmwork n slin to ompr ginst. RgPl irst trnsorms th strutur ASIC plmnt prolm into simplr row-s plmnt prolm y rsizing th lrgr lls (REG n RAM to unit siz n rmoving th physil sp rsrv or ths lls rom th pltorm. Also, th lok onstrints r ignor t this stg. Existing high qulity row-s plr (suh s CAPO [4], mpl6 [5] t) is us to gnrt n initil plmnt with xllnt wirlngth. Th plmnt rsults r thn xpn to r-insrt physil sp rmov or REG n RAM lls whil onurrntly prorming ut minimiztion u to rinsrt sp or ths lls. An intgr linr progrmming (ILP) s lok ssignmnt n ntwork low s lok lgliztion is prorm to stisy th lok onstrints. Finlly wirlngth rution is prorm to uno ny mg u to lgliztion. 3. LEAKAGE/CLOCK POWER MODEL Lkg Powr Mol: Th lkg powr o strutur ASIC pltorm is roughly proportionl to th numr o vis in it. Evn i no ll (in th RTL) is mpp on to vi on th pltorm, th vi will still onsum lkg powr unlss isonnt rom th powr supply. Existing strutur ASICs lry llow powr own (i.. isonnt rom powr gri) o unus vis on th pltorm using singl-vi powr progrmming. W ssum tht powr-own n prorm t two lvls o grnulrity: ) An unus til n ompltly powr own ruing its lkg (n ynmi) powr to zro, n ) Within til, n unus olumn n powr own i no untioning lls r pl in it, ruing its powr to zro. Th lkg powr svings hiv y powr own o omplt til is quivlnt to tht hiv y iniviul powr own o h olumn in th til iniviully. I th lkg powr o on olumn is P ol, thn th lkg powr mol o th strutur ASIC pltorm is simply th sum o lkg powr o ll th olumns tht 0 r not powr 1 own. P lk = P ol X B X E A (1) t tils ols(t) whr ols(t) nots th olumns in til t n E is inry vril whos vlu is 1 i th olumn is powr on n 0 othrwis. From Eqn 1, it is lr tht w shoul try to minimiz th numr o olumns powr up to ru lkg powr. Clok Powr Mol: Unlik lkg powr, lok powr is lrgly proportionl to th lok swith pitn. Du to stringnt slw n skw onstrints on th lok signl, lok is istriut ross th pltorm using hirrhy o high riv powr hungry urs. To ru lok powr, th im shoul to ru lok ntwork s swith pitn. To unrstn th lok powr mol, w must irst unrstn lok istriution rhittur. W ssum simplisti lok istriution ntwork s pit in Figur 2 sri using 2x2 tils to ru luttr. Figur 2- pits th pltorm lvl lok istriution whrs Figur 2- pits th til lvl lok istriution. Th rhittur w ssum is s on th rnt works on lok istriution on FPGAs [6] [7]. Hr, w sri th lok istriution rhittur o singl lok whih is uplit to istriut multipl loks. In Figur 2-, lvl 1 ur B1 insrts th lok signl t th ntr o th hip tht rivs horizontl spin. Eh lvl 2 ur B2 istriuts th lok signl to on vrtil spin. Similrly, lvl 3 urs rivs th lok signl into h til. Insi til, s shown in Figur 2-, Lvl 4 urs B4 riv th DFF olumns (only 1 shown) s wll s REG n RAM lls. Owing to th lrgr numr o squntil lmnts in RAM n REG lls, multipl B4 urs r rquir to riv thm (only 396

3 B2 B2 B1 B2 B2 B4 DFF DFF DFF B4 RAM ) ) REG Figur 2: Clok istriution: ) Pltorm ) Til lvl 1 shown). W ssum tht h B4 ur n riv only s mny squntil lmnts s r in DFF olumn. To istriut multipl loks, th B1 n B2 lok urs n rplit or h lok signl. Du to routing onstrints, typilly only sust o pltorm lvl loks n rout into h til. Eh n B4 lok urs is rplit s mny tims s th siz o sust o loks tht n rout in h til. W ssum tht powr-own o lok signl n prorm t thr lvls o grnulrity: ) An unus vrtil spin s lok n isonnt i ll o th tils rivn y this spin r unus. ) An unus til n isonnt i ll lls in it r unus, n ) within th til, th lok riving h DFF olumn, REG, RAM ll n isonnt. For pltorm with WxH tils (inst o 2x2 in Figur 2), lt C G loks t pltorm lvl n C T loks t til lvl support. Furthr, lt th numr o quivlnt (tr sling or lrgr sizs o REG n RAM) numr o DFF olumns S h ontining N squntil lmnts. Unr ths ssumptions, Tl 1, shows th onstitunts o th lok ntwork. Columns 2 ontins th numr o ur n whrs olumn 3 shows th pitiv lo on h o ths urs. Th lst olumn shows th totl swith pitn sn y th orrsponing lvl o lok urs whn th input pitn o n ntity X is not y L X. B4 Tl 1: Clok Tr Distriution Chrtristis Bur Numr Eh Totl Typ Instn Lo Lo B1 C G 2 W L B2 2 W C G L B2 B2 C G 2 W 0.5 H L 2 W H C G L C T W H S L B4 W H S C T L B4 B4 C T W H S N L DF F W H S N C T L DF F Using th lok ntwork rhittur n Tl 1, th totl lok powr n writtn s!! C X G 2WX 0.5H X P lk = L B1 + E ijl B2 + (E ije jk L ) + i=0 X t tils C T X m=0 j=0 k=0!! SX (E mnl B4 + E mnl DF F) n=0 whr ll E xy r ooln vrils. E ij is 1 i lok i rivs spin j, E jk is 1 i spin j rivs til k on tht spin, E mn is 1 i lok m in th til rivs th olumn n. Th irst trm in Eqution 2 is th totl swith pitn o C G glol loks n th son trm is th totl swith pitn within til, summ ovr ll th tils. Sltiv powr own o unus omponnts (spin, til, olumn) moult th vlus o ths inry vril thus hnging th lok powr. (2) 4. LOW POWER PLACEMENT W now introu th prolm ing tkl in this work. Givn strutur ASIC pltorm n sign, prorm ll plmnt to minimiz th lok n lkg powr onsumption y mximizing th omponnts tht n powr own. Powr rution shoul not gr th wirlngth y mor thn givn ugt. 4.1 Ovrll Flow Figur 3, shows our omplt low. Th rtngulr loks rprsnt our nw ontriutions whrs th ovl loks rprsnt th stps in RgPl [1], n xisting opn sour plr or strutur ASICs. Atr sriing th ovrll low in this stion, h rtngulr lok will xplin in mor tils in nxt w sustions. RTL Spin & Til Rution Pltorm Glol Plmnt Clok Lgliztion Column Minimiztion Column Assignmnt Wirlngth Rution OUT Figur 3: Our plmnt low. Blu rtngls r our nw ontriutions. Gry ovls r rom [1]. Givn th input ntlist n th pltorm, w minimiz th vrtil spins n tils tht must rmin powr up y gnrting nw onstrints or glol plr. This stp works unr givn wirlngth inrs ugt. Glol plmnt is thn xut on th sign ollow y lok lgliztion. In th nxt stp, w minimiz th numr o olumns tht must sty powr on y voiing snrios whr th numr o lls in til is slightly mor thn intgrl multipl o numr o lls tht n ommot in olumn, thry rquiring nothr olumn. Finlly, w lustr n ssign th lls into s w olumns s possil whil minimizing wirlngth hng. 4.2 Spin n Til Rution To mrk vrtil spin s unus, w must nsur tht ll th tils rivn y th spin r mrk s unus. To mrk til s unus, w must mk sur tht no ll is pl in it. I th sign to pl is muh smllr thn th physil pltorm, nturlly thr woul mny suh tils. Howvr, our im is to mximiz suh unus tils y intiying thos whih woul hv vry low numr o lls in thm n viting ths lls without muh wirlngth pnlty. Algorithm 1 pits our ovrll spins n til rution strtgy. W prorm rough plmnt to gnrt ors nsity mp nsuring tht th ut-lin uring prtitioning oini with th til ounris (Lin 1). Th wirlngth inrs ugt is st to k% o th originl wirlngth (Lin 2). For h horizontl trunk in th pltorm, w go ovr ll th vrtil spins onnt to it. Ths spins r sort in nonrsing orr o th numr o lls in ll th tils rivn y th orrsponing vrtil spin (Lin 4-5). Thn, th sort st o spins is itrt ovr whil trying to vit th lls in it using prour EvitSpin. Th shm or ruing th numr o tils is lso similr (Lin 8-10) whrin th prour EvitTil is xut or h til in sort orr. W now sri Algorithm 2 n Algorithm 3 whih implmnt prour EvitSpin n EvitTil rsptivly. 397

4 Algorithm 1 Vrtil Spin n Til Minimiztion 1: Prorm Rough Plmnt 2: BUDGET = k % o wirlngth o sign {Minimiz spin utiliztion in nxt lok} 3: or ll Horizontl Spin hs o 4: CONN = All vrtil spins onnt to hs 5: Sort CONN y numr o lls in it 6: or ll Vrtil Spin vs onnt to CONN o 7: EvitSpin(vs, BUDGET) {Minimiz til utiliztion in nxt lok} 8: T = All tils in pltorm 9: Sort TILES y numr o lls in it 10: or ll Til t in TILES o 11: EvitTil(vs, BUDGET) Algorithm 2 EvitSpin(Spin S, BUDGET) 1: SL(SR) = Spin on lt(right) o S 2: REST = Tils in SL SR 3: or ll Til t in S o 4: NGHBR = All tils in REST <= 1 til wy rom t 5: Buil low twn t n NGHBR 6: A Constrint or WL Inrs < BUDGET 7: i Flow Possil thn 8: Mov lls rom tils in S to SL or SR Algorithm 2 whih tris to vit givn spin works s ollows. For trgt urrnt spin ing vit, th list o ll tils in th spins to th lt n right o it is otin (Lins 1-2). Nxt w writ ntwork low ormultion whr ll th lls rom h til longing to th urrnt spin r mov out o th spin. For h til in th spin, th possil lotion o intrst r ll th til jnt to it xpt itsl (Lin 3-5). W limit th lls to mov to only jnt tils to ru wirlngth pnlty. Th ojtiv o th ntwork low is to minimiz th stimt wirlngth inrs u to th movmnt. An itionl onstrint is to oun th mximum ptl wirlngth inrs (Lin 6). I th ntwork low is possil, th spin S n vit n its lls r mov out. Algorithm 3 EvitTil (til T, BUDGET) 1: Gt xavg = vrg X oorint o lls in T 2: Gt yavg = vrg Y oorint o lls in T 3: Comput Up/Dn/L/RtConn or T 4: NGHBR = All nighors o tils T 5: or ll tils n in NGHBR o 6: i n is n mpty til, ontinu; 7: movx = n s ntr X oorint - xavg 8: movy = n s ntr Y oorint - yavg 9: WLINCR = movx (LConn - RtConn) 10: WLINCR += movy (DnConn - UpConn) 11: A low rom T to n with ost WLINCR 12: A Constrint or WL Inrs < BUDGET 13: i Flow Possil thn 14: Evit T n mov lls Algorithm 2 n only vit on whol spin t tim. Howvr, thr n mny snrios whr w (ut not ll) tils o spin hv smll numr o lls in it n n vit. For this, Algorithm 3 works on h til in th sign. For h til, w in th vrg x n y oorint (XAvg n YAvg) o th lls in it (Lin 1-2). W lso omput our numrs (Rt- Conn, UpConn, LConn, DnConn) whih rprsnt th numr o nts inint on ny ll in th til whos ouning ox is stritly to th right, ov, on lt, or low this til (Lin 3). Th intuition is tht i ll th lls o this til r mov to nothr til, th inrs in wirlngth y this mov n pproximt y omintion o ths numrs. Nxt, w itrt ovr ll ight physilly ontiguous tils roun th trgt til (Lin 5) whih r th possil stintions whil omputing th stimt wirlngth inrs (Lin 7-10). A ntwork low prolm is uilt n i thr is lgl solution to it, th til T n vit (Lin 13-14). Atr th trmintion o Algorithm 1, w otin th lrgst st o omplt spins n tils whih n vit unr givn wirlngth inrs ugt. Bs on this inormtion, w trnsorm th plmnt prolm y ing ix lokgs ovring th unus tils. This trnsorm plmnt prolm oms th input to RgPl glol plr. 4.3 Column Minimiztion Atr th glol plmnt n lok lgliztion hs n prorm, omintionl (i.. LOGC) n squntil lls longing to multipl loks oul istriut in h til. To xploit this lxiility, w pply Algorithm 4 to rtngulr pphol M tils wi n N tils high. On th numr o powr up olumns in th pphol is ru, th pphol is mov to th nxt jnt position n Algorithm 4 is rrun. I th whol pltorm onsists tils tht is W wi n H high, Algorithm 4 is xut W-M H-N tims. Now w sri th Algorithm 4 Column Count Rution 1: T = All tils in urrnt pphol 2: N = Mximum lls in olumn 3: C = All loks in T NIL { NIL Clok onnts to omintionl ll i.. LOGCs} {Lt n i = lls o lok in til i} 4: or ll Clok C o 5: MOVES = φ 6: USED = P i T il(ni/n) 7: REQD = il( P i T ni)/n 8: i USED == REQD thn 9: ontinu; {Column ount lry optimiz} 10: or ll Til t T o 11: t.extr = n t - N loor(n t/n) 12: Sort T in non inrsing orr o Extr(t) 13: or ll Til t sort T o 14: OTHER(t) = T - {t}. Sort w.r.t. istn rom t. 15: or ll Til o sort OTHER o 16: trns = min(t.extr, N-o.Extr) 17: MOVES = MOVES {trns rom t to o} 18: i t.extr == 0 thn 19: rk 20: Implmnt ll MOVES stor stps involv in on invotion: W ummy lok ll NIL whih onnts to ll omintionl lls (i.. LOGC lls) (Lin 3). Th optimiztion is prorm or on lok typ t tim (Lin 4). Th mximum numr o lls tht n ommot in olumn is givn s N (Lin 2). W prun th ss or whih th numr o olumns oupi is lry optiml (Lin 6-9). For h til in th pphol, w omput th minimum ount o lls (Extr) tht, whn rmov, lv n intgrl multipl o N lls (Lin 10-11). All th tils in th pphol r sort oring to non-rsing Extr ount 398

5 (Lin 12). For h til, vry til xpt itsl is prosptiv til in whih th Extr lls n mov (Lin 14). To ru th impt on wirlngth inrs, w sort th prosptiv tils oring to istn rom th urrnt til (Lin 15) n try pushing th Extr lls o urrnt til into thm s long s this mov os not rt nw olumns in th prosptiv til (Lin 17-18). On ll th movs to ru th olumn ount or lok r ror, w tully implmnt thm y moving th lls mong th tils. Whn moving ll rom til A to til B, its nw lotion in til B is hosn s th point losst to th originl lotion in til A. 4.4 Column Assignmnt Atr th trmintion o Algorithm 4, th ision rgring lustring o ths lls into olumns n how th olumns or th irnt loks r rltivly pl, still ns to m. For this, w us Algorithm 5 whih runs on on til t tim n pks th lls into iniviul olumns. Algorithm 5 irst Algorithm 5 WL Awr Column Assignmnt 1: COLS = Columns in th til 2: N = Cpity o h olumn 3: BINS = φ 4: C = All loks in til NIL { NIL Clok onnts to omintionl ll i.. LOGCs} 5: or ll Clok C o 6: CLSTR = φ 7: L = lls o lok rom lt to right 8: or ll Cll i L o 9: CLSTR = CLSTR i 10: i siz o CLSTR == N thn 11: BINS = BINS CLSTR 12: CLSTR = φ 13: Assign BINS to COLS [ssignmnt prolm]. Cost o ssignmnt = inint wirlngth. 14: Swp lls twn olumns o sm lok to ru WL prorms gry lustring o lls o sm lok typ into ins o siz N (=pity o h olumn) strting th swp rom th lt g o th til (Lin 9-12). All th lls longing to on in orm on lustr n pl in on olumn. I th numr o ins us or pking is n th numr o olumns vill in th til is n, mpping th ins to n olumns n st s n Assignmnt Prolm n solv iintly using Munkrs lgorithm (Lin 13). Finlly, to rpir wirlngth grtion u to su-optiml lustring o lls into olumns, lls r swpp twn olumns o sm lok typ i it rus wirlngth. ) Input ) Clustring ) Colm Assign. ) WL Rution Figur 4: Column ssignmnt: ) Input. ) Clls lustr s on originl lotion. ) Columns ssign to h lustr. ) Atr WL rution y swpping Figur 4 shows n xmpl o olumn pking in tion. For this xmpl, h olumn n hv only 2 lls. Clls rivn y th sm lok typ hv th sm shp. Th lls r ivi in thr ins s shown in Figur 4-. Ths ins r ssign to iniviul olumns s shown in Figur 4-. Finlly, ll swpping my l to swpping o lls n to ru wirlngth. 5. EXPERIMENTAL SETUP W implmnt our low powr plmnt low PASAP in th C++ lngug insi th opn sour strutur ASIC plmnt tool RgPl [1]. All xprimnts wr run on 16 or, 1.6 GHz, Linux worksttion. W us GLPK [8] s th intgr linr progrmming (ILP) n ntwork low solvr n ustom implmnttion o Munkrs [9] lgorithm or ssignmnt prolm. Th wirlngth inrs ugt in Algorithm 1 ws st t 15%. Pltorm: Two irnt pltorms wr gnrt y rpliting th til sri in Stion 2.2. Th tils o ths pltorms r in Tl 2. Columns 2 n 3 show th numr o tims th til is rplit in horizontl n vrtil irtion rsptivly. Rst o th olumns init th mximum numr o LOGC, DFF, REG, RAM tht n ommot in th pltorm. Tl 2: Pltorm Chrtristis Plt Rp Rp Mx Mx Mx Mx Mx Nm X Y LOGC DFF REG RAM CLK A M 675k B M 811k Dsigns: Th nhmrks us wr originl rls y ASIC or th plmnt ontst. Tl 3 shows th rkup o th sign in trms o onstitunt lls. Th totl numr o lls rngs twn 125K to ovr 1 million. Column 6 shows th numr o glol lok signls us. Tl 3: Bnhmrk Chrtristis Nm LOGC DFF REG RAM CLK si1 832,824 87, si2 812,200 45, si3 961,063 52, si4 102,038 23, si5 913,853 84, RESULTS Tl 4 sris our xprimntl rsults ompring th plmnt gnrt y RgPl to PASAP plmnt. Th nhmrk nm in th irst olumn lso shows th pltorm on whih th nhmrk ws pl. For xmpl si4b intiis tht it is th nhmrk si4 pl on pltorm B. Th mtris ing ompr or th two plmnt r : ) unus spins, ) unus tils, ) unus olumns, ) wirlngth n ) totl CPU runtim. For h o ths mtris, thr su-olumns r shown in Tl 4. Ths su-olumns pit th vlu otin using RgPl (RP in tl), vlu otin using PASAP (PA in tl) n th irn twn ths two solutions rsptivly. Th iy opasap to inrs th numr o unus spins, tils n olumns is vint rom Tl 4. Du to th irnt nhmrk sizs n utiliztion rtio, th numrs vry wily mong th irnt iruits. Thror, in our isussion, w will primrily ous on th improvmnt/pnlty summ ovr ll th nhmrks. First o ll, w not tht ovr ll th nhmrks, nrly 58% xtr lok spins n turn o using 399

6 Tl 4: Inrs in numr o spin, til n olumn tht n powr own or vrious nhmrks. Bnh # Unus Spins # Unus Tils # Unus Columns Wirlngth (x10 6 ) CPU Runtim (s) Nm RP PA % RP PA % RP PA % RP PA % RP PA % si1a in si1b si2a 0 3 in si2b si3b si4a si4b si5b 0 4 in Totl: our mtho. Turning o spin irtly orrspons to lowr lok pitn. Bnhmrks si1a n si3b hs suh high utiliztion rtio tht oth RgPl n PASAP nnot in vn on unus spin. Similrly, th numr o unus tils n inrs y roun 29% thus giving signiint nhnmnt in th powr sving ility. As or th numr o unus olumns, thir numr improv y pproximtly 42% using PASAP s ompr to RgPl. Th vry low improvmnt in th numr o olumn us or nhmrk si4a n si4b is u to its vry smll siz whih implis vn y using RgPl, most o th olumns r unus. Th ov improvmnt in inrsing th ount o unus spin, tils n olumn oms t ost s sn in th wirlngth n runtim pnlty. Th wirlngth o th signs inrs y pproximtly 17%. Du to th runtim ssoit with rough plmnt gnrtion n ggrssiv spin/til/olumn rution, PASAP tks pproximtly 30% mor runtim tht RgPl. Though runtim grtion is not insigniint, w liv it is ir tr-o or th kin o powr svings possil with PASAP. To ompr th powr rution, th hng in plmnt mtris rom Tl 4 must onvrt to lok n lkg powr. Using th rltion riv in Eqn 1, th lkg powr sving hiv y prorming plmnt using PASAP s ompr to RgPl is plott in Figur 5. Eh olumn in Figur 5 orrspons to on nhmrk with th xption o lst olumn whih shows th vrg svings. PASAP rus th lkg powr in th rng o 7% to 40% with n vrg vlu o 17%. L k g R u tio n ( in % ) B n h m r k ( si * ) Figur 5: Lkg powr svings or plmnt gnrt y PASAP ompr to RgPl. Nxt w ompr th lok powr rution u to PASAP. By ggrssiv rution in th numr o spins, tils n olumns in whih th lok signl ns to istriut, PASAP n signiintly minimiz th lok swith pitn. Bs on th lok powr xprssion riv in Eqn 2, w plott th lok powr rution hiv y PASAP or irnt nhmrks in Figur 6. PASAP rus th lok powr o irnt nhmrk iruits in th rng o 20% to 60% with n vrg vlu o 32%. Th lok powr ws omput ssuming th rqunis o ll th lok signl in th strutur ASIC is th sm. C lo k P o w r R u tio n ( in % ) B n h m r k ( si * ) Figur 6: Clok powr svings or plmnt gnrt y PASAP ompr to RgPl. 7. CONCLUSIONS In this ppr, w propos powr wr strutur ASIC plmnt (PASAP) low. For givn strutur ASIC rhittur, PASAP minimizs th lkg powr n lok powr issiption y mximizing th vis tht n powr own n ruing th lok ntwork s swith pitn rsptivly. W propos lgorithms to minimiz th numr o lok spins, tils (th uiling lok o strutur ASIC pltorm) n olumns tht n to powr on, without signiintly impting th wirlngth o th sign. Exprimntl rsults on lrg tstss show tht PASAP n ru th lkg n lok powr onsumption y s muh s 40% n 60% rsptivly with 17% pnlty in wirlngth n 30% longr plr runtim. 8. REFERENCES [1] A. Chkrorty t l., Rgpl: A high qulity opn-sour plmnt rmwork or strutur sis, in Dsign Automtion Conrn, pp , ACM, [2] H. Shmit t l., Plmnt Chllngs or Strutur ASICs, in Intrntionl Symposium on Physil sign, pp , ACM, [3] ASIC Corport Wsit. [4] J. A. Roy t l., Cpo: Roust n Sll Opn-sour min-ut Floorplr, in Intrntionl Symposium on Physil sign, pp , ACM, [5] T. F. Chn t l., mpl6: Enhn Multilvl Mix-siz Plmnt, in Intrntionl Symposium on Physil sign, pp , ACM, [6] Q. Wng t l., Clok powr rution or virtx-5 pgs, in Proing o th Intrntionl Symposium on Fil Progrmml Gt Arrys, (Nw York, NY, USA), pp , ACM, [7] L. Wng t l., Fpg ynmi powr minimiztion through plmnt n routing onstrints, EURASIP J. Em Syst., vol. 2006, no. 1, pp. 7 7, [8] GNU Linr Progrmming Kit. [9] H. W. Kuhn, Th Hungrin Mtho or th Assignmnt Prolm, Nvl Rsrh Logistis Qurtrly, vol. 2, pp ,

Present state Next state Q + M N

Present state Next state Q + M N Qustion 1. An M-N lip-lop works s ollows: I MN=00, th nxt stt o th lip lop is 0. I MN=01, th nxt stt o th lip-lop is th sm s th prsnt stt I MN=10, th nxt stt o th lip-lop is th omplmnt o th prsnt stt I

More information

COMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS

COMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS OMPLXITY O OUNTING PLNR TILINGS Y TWO RS KYL MYR strt. W show tht th prolm o trmining th numr o wys o tiling plnr igur with horizontl n vrtil r is #P-omplt. W uil o o th rsults o uquir, Nivt, Rmil, n Roson

More information

12. Traffic engineering

12. Traffic engineering lt2.ppt S-38. Introution to Tltrffi Thory Spring 200 2 Topology Pths A tlommunition ntwork onsists of nos n links Lt N not th st of nos in with n Lt J not th st of nos in with j N = {,,,,} J = {,2,3,,2}

More information

An undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V

An undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V Unirt Grphs An unirt grph G = (V, E) V st o vrtis E st o unorr gs (v,w) whr v, w in V USE: to mol symmtri rltionships twn ntitis vrtis v n w r jnt i thr is n g (v,w) [or (w,v)] th g (v,w) is inint upon

More information

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review rmup CSE 7: AVL trs rmup: ht is n invrint? Mihl L Friy, Jn 9, 0 ht r th AVL tr invrints, xtly? Disuss with your nighor. AVL Trs: Invrints Intrlu: Exploring th ln invrint Cor i: xtr invrint to BSTs tht

More information

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths. How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0

More information

Exam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013

Exam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013 CS Avn Dt Struturs n Algorithms Exm Solution Jon Turnr //. ( points) Suppos you r givn grph G=(V,E) with g wights w() n minimum spnning tr T o G. Now, suppos nw g {u,v} is to G. Dsri (in wors) mtho or

More information

CSC Design and Analysis of Algorithms. Example: Change-Making Problem

CSC Design and Analysis of Algorithms. Example: Change-Making Problem CSC 801- Dsign n Anlysis of Algorithms Ltur 11 Gry Thniqu Exmpl: Chng-Mking Prolm Givn unlimit mounts of oins of nomintions 1 > > m, giv hng for mount n with th lst numr of oins Exmpl: 1 = 25, 2 =10, =

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

Constructive Geometric Constraint Solving

Constructive Geometric Constraint Solving Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC

More information

Planar Upward Drawings

Planar Upward Drawings C.S. 252 Pro. Rorto Tmssi Computtionl Gomtry Sm. II, 1992 1993 Dt: My 3, 1993 Sri: Shmsi Moussvi Plnr Upwr Drwings 1 Thorm: G is yli i n only i it hs upwr rwing. Proo: 1. An upwr rwing is yli. Follow th

More information

b. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s?

b. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s? MATH 3012 Finl Exm, My 4, 2006, WTT Stunt Nm n ID Numr 1. All our prts o this prolm r onrn with trnry strings o lngth n, i.., wors o lngth n with lttrs rom th lpht {0, 1, 2}.. How mny trnry wors o lngth

More information

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely . DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,

More information

Module graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura

Module graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura Moul grph.py CS 231 Nomi Nishimur 1 Introution Just lik th Python list n th Python itionry provi wys of storing, ssing, n moifying t, grph n viw s wy of storing, ssing, n moifying t. Bus Python os not

More information

1 Introduction to Modulo 7 Arithmetic

1 Introduction to Modulo 7 Arithmetic 1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w

More information

Paths. Connectivity. Euler and Hamilton Paths. Planar graphs.

Paths. Connectivity. Euler and Hamilton Paths. Planar graphs. Pths.. Eulr n Hmilton Pths.. Pth D. A pth rom s to t is squn o gs {x 0, x 1 }, {x 1, x 2 },... {x n 1, x n }, whr x 0 = s, n x n = t. D. Th lngth o pth is th numr o gs in it. {, } {, } {, } {, } {, } {,

More information

A Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation

A Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation A Simpl Co Gnrtor Co Gnrtion Chptr 8 II Gnrt o for singl si lok How to us rgistrs? In most mhin rhitturs, som or ll of th oprnsmust in rgistrs Rgistrs mk goo tmporris Hol vlus tht r omput in on si lok

More information

Why the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1.

Why the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1. Why th Juntion Tr lgorithm? Th Juntion Tr lgorithm hris Willims 1 Shool of Informtis, Univrsity of Einurgh Otor 2009 Th JT is gnrl-purpos lgorithm for omputing (onitionl) mrginls on grphs. It os this y

More information

Seven-Segment Display Driver

Seven-Segment Display Driver 7-Smnt Disply Drivr, Ron s in 7-Smnt Disply Drivr, Ron s in Prolm 62. 00 0 0 00 0000 000 00 000 0 000 00 0 00 00 0 0 0 000 00 0 00 BCD Diits in inry Dsin Drivr Loi 4 inputs, 7 outputs 7 mps, h with 6 on

More information

EE1000 Project 4 Digital Volt Meter

EE1000 Project 4 Digital Volt Meter Ovrviw EE1000 Projt 4 Diitl Volt Mtr In this projt, w mk vi tht n msur volts in th rn o 0 to 4 Volts with on iit o ury. Th input is n nlo volt n th output is sinl 7-smnt iit tht tlls us wht tht input s

More information

The University of Sydney MATH2969/2069. Graph Theory Tutorial 5 (Week 12) Solutions 2008

The University of Sydney MATH2969/2069. Graph Theory Tutorial 5 (Week 12) Solutions 2008 Th Univrsity o Syny MATH2969/2069 Grph Thory Tutoril 5 (Wk 12) Solutions 2008 1. (i) Lt G th isonnt plnr grph shown. Drw its ul G, n th ul o th ul (G ). (ii) Show tht i G is isonnt plnr grph, thn G is

More information

CSE 373. Graphs 1: Concepts, Depth/Breadth-First Search reading: Weiss Ch. 9. slides created by Marty Stepp

CSE 373. Graphs 1: Concepts, Depth/Breadth-First Search reading: Weiss Ch. 9. slides created by Marty Stepp CSE 373 Grphs 1: Conpts, Dpth/Brth-First Srh ring: Wiss Ch. 9 slis rt y Mrty Stpp http://www.s.wshington.u/373/ Univrsity o Wshington, ll rights rsrv. 1 Wht is grph? 56 Tokyo Sttl Soul 128 16 30 181 140

More information

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim's Alorithm Introution Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #33 3 Alorithm Gnrl Constrution Mik Joson (Univrsity o Clry)

More information

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018 CSE 373: Mor on grphs; DFS n BFS Mihl L Wnsy, F 14, 2018 1 Wrmup Wrmup: Disuss with your nighor: Rmin your nighor: wht is simpl grph? Suppos w hv simpl, irt grph with x nos. Wht is th mximum numr of gs

More information

Math 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes.

Math 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes. Nm: UCA ID Numr: Stion lttr: th 61 : Disrt Struturs Finl Exm Instrutor: Ciprin nolsu You hv 180 minuts. No ooks, nots or lultors r llow. Do not us your own srth ppr. 1. (2 points h) Tru/Fls: Cirl th right

More information

Register Allocation. Register Allocation. Principle Phases. Principle Phases. Example: Build. Spills 11/14/2012

Register Allocation. Register Allocation. Principle Phases. Principle Phases. Example: Build. Spills 11/14/2012 Rgistr Allotion W now r l to o rgistr llotion on our intrfrn grph. W wnt to l with two typs of onstrints: 1. Two vlus r liv t ovrlpping points (intrfrn grph) 2. A vlu must or must not in prtiulr rhitturl

More information

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h

More information

Clustering Techniques for Coarse-grained, Antifuse-based FPGAs

Clustering Techniques for Coarse-grained, Antifuse-based FPGAs Clustring Thniqus or Cors-grin, Antius-s FPGAs Chng-woo Kng n Mssou Prm Astrt In this ppr, w prsnt r n prormn-rivn lustring thniqus or ors-grin, ntius-s FPGAs. A mro logi ll in this lss o FPGAs hs multipl

More information

0.1. Exercise 1: the distances between four points in a graph

0.1. Exercise 1: the distances between four points in a graph Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 pg 1 Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 u: W, 3 My 2017, in lss or y mil (grinr@umn.u) or lss S th wsit or rlvnt mtril. Rsults provn in th nots, or in

More information

Outline. Computer Science 331. Computation of Min-Cost Spanning Trees. Costs of Spanning Trees in Weighted Graphs

Outline. Computer Science 331. Computation of Min-Cost Spanning Trees. Costs of Spanning Trees in Weighted Graphs Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim s Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #34 Introution Min-Cost Spnnin Trs 3 Gnrl Constrution 4 5 Trmintion n Eiiny 6 Aitionl

More information

QUESTIONS BEGIN HERE!

QUESTIONS BEGIN HERE! Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt o Computr n Inormtion Sins CSCI 2710 (Trno) Disrt Struturs TEST or Sprin Smstr, 2005 R this or strtin! This tst is los ook

More information

CS 461, Lecture 17. Today s Outline. Example Run

CS 461, Lecture 17. Today s Outline. Example Run Prim s Algorithm CS 461, Ltur 17 Jr Si Univrsity o Nw Mxio In Prim s lgorithm, th st A mintin y th lgorithm orms singl tr. Th tr strts rom n ritrry root vrtx n grows until it spns ll th vrtis in V At h

More information

Garnir Polynomial and their Properties

Garnir Polynomial and their Properties Univrsity of Cliforni, Dvis Dprtmnt of Mthmtis Grnir Polynomil n thir Proprtis Author: Yu Wng Suprvisor: Prof. Gorsky Eugny My 8, 07 Grnir Polynomil n thir Proprtis Yu Wng mil: uywng@uvis.u. In this ppr,

More information

V={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}

V={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)} s s of s Computr Sin & Enginring 423/823 Dsign n Anlysis of Ltur 03 (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) s of s s r strt t typs tht r pplil to numrous prolms Cn ptur ntitis, rltionships twn

More information

V={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}

V={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)} Introution Computr Sin & Enginring 423/823 Dsign n Anlysis of Algorithms Ltur 03 Elmntry Grph Algorithms (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) I Grphs r strt t typs tht r pplil to numrous

More information

OpenMx Matrices and Operators

OpenMx Matrices and Operators OpnMx Mtris n Oprtors Sr Mln Mtris: t uilin loks Mny typs? Dnots r lmnt mxmtrix( typ= Zro", nrow=, nol=, nm="" ) mxmtrix( typ= Unit", nrow=, nol=, nm="" ) mxmtrix( typ= Int", nrow=, nol=, nm="" ) mxmtrix(

More information

Algorithmic and NP-Completeness Aspects of a Total Lict Domination Number of a Graph

Algorithmic and NP-Completeness Aspects of a Total Lict Domination Number of a Graph Intrntionl J.Mth. Comin. Vol.1(2014), 80-86 Algorithmi n NP-Compltnss Aspts of Totl Lit Domintion Numr of Grph Girish.V.R. (PES Institut of Thnology(South Cmpus), Bnglor, Krntk Stt, Ini) P.Ush (Dprtmnt

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski

DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski Dut with Dimons Brlt DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Lsli Roglski Photo y Anrw Wirth Supruo DUETS TM from BSmith rt olor shifting fft tht mks your work tk on lif of its own s you mov! This

More information

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas SnNCutCnvs Using th Printl Stikr Funtion On-o--kin stikrs n sily rt y using your inkjt printr n th Dirt Cut untion o th SnNCut mhin. For inormtion on si oprtions o th SnNCutCnvs, rr to th Hlp. To viw th

More information

Designing A Concrete Arch Bridge

Designing A Concrete Arch Bridge This is th mous Shwnh ri in Switzrln, sin y Rort Millrt in 1933. It spns 37.4 mtrs (122 t) n ws sin usin th sm rphil mths tht will monstrt in this lsson. To pro with this lsson, lik on th Nxt utton hr

More information

QUESTIONS BEGIN HERE!

QUESTIONS BEGIN HERE! Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt of Computr n Informtion Sins CSCI 710 (Trnoff) Disrt Struturs TEST for Fll Smstr, 00 R this for strtin! This tst is los ook

More information

Graph Isomorphism. Graphs - II. Cayley s Formula. Planar Graphs. Outline. Is K 5 planar? The number of labeled trees on n nodes is n n-2

Graph Isomorphism. Graphs - II. Cayley s Formula. Planar Graphs. Outline. Is K 5 planar? The number of labeled trees on n nodes is n n-2 Grt Thortil Is In Computr Sin Vitor Amhik CS 15-251 Ltur 9 Grphs - II Crngi Mllon Univrsity Grph Isomorphism finition. Two simpl grphs G n H r isomorphi G H if thr is vrtx ijtion V H ->V G tht prsrvs jny

More information

Nefertiti. Echoes of. Regal components evoke visions of the past MULTIPLE STITCHES. designed by Helena Tang-Lim

Nefertiti. Echoes of. Regal components evoke visions of the past MULTIPLE STITCHES. designed by Helena Tang-Lim MULTIPLE STITCHES Nrtiti Ehos o Rgl omponnts vok visions o th pst sign y Hln Tng-Lim Us vrity o stiths to rt this rgl yt wrl sign. Prt sping llows squr s to mk roun omponnts tht rp utiully. FCT-SC-030617-07

More information

12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem)

12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem) 12/3/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 Ciruits Cyl 2 Eulr

More information

5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs

5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs Prt 10. Grphs CS 200 Algorithms n Dt Struturs 1 Introution Trminology Implmnting Grphs Outlin Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 2 Ciruits Cyl A spil yl

More information

(a) v 1. v a. v i. v s. (b)

(a) v 1. v a. v i. v s. (b) Outlin RETIMING Struturl optimiztion mthods. Gionni D Mihli Stnford Unirsity Rtiming. { Modling. { Rtiming for minimum dly. { Rtiming for minimum r. Synhronous Logi Ntwork Synhronous Logi Ntwork Synhronous

More information

New challenges on Independent Gate FinFET Transistor Network Generation

New challenges on Independent Gate FinFET Transistor Network Generation Nw hllngs on Inpnnt Gt FinFET Trnsistor Ntwork Gnrtion Viniius N. Possni, Anré I. Ris, Rnto P. Ris, Flip S. Mrqus, Lomr S. Ros Junior Thnology Dvlopmnt Cntr, Frl Univrsity o Plots, Plots, Brzil Institut

More information

COMP108 Algorithmic Foundations

COMP108 Algorithmic Foundations Grdy mthods Prudn Wong http://www.s.liv..uk/~pwong/thing/omp108/01617 Coin Chng Prolm Suppos w hv 3 typs of oins 10p 0p 50p Minimum numr of oins to mk 0.8, 1.0, 1.? Grdy mthod Lrning outoms Undrstnd wht

More information

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1 CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml

More information

CS 241 Analysis of Algorithms

CS 241 Analysis of Algorithms CS 241 Anlysis o Algorithms Prossor Eri Aron Ltur T Th 9:00m Ltur Mting Lotion: OLB 205 Businss HW6 u lry HW7 out tr Thnksgiving Ring: Ch. 22.1-22.3 1 Grphs (S S. B.4) Grphs ommonly rprsnt onntions mong

More information

S i m p l i f y i n g A l g e b r a SIMPLIFYING ALGEBRA.

S i m p l i f y i n g A l g e b r a SIMPLIFYING ALGEBRA. S i m p l i y i n g A l g r SIMPLIFYING ALGEBRA www.mthltis.o.nz Simpliying SIMPLIFYING Algr ALGEBRA Algr is mthmtis with mor thn just numrs. Numrs hv ix vlu, ut lgr introus vrils whos vlus n hng. Ths

More information

Outline. Binary Tree

Outline. Binary Tree Outlin Similrity Srh Th Binry Brnh Distn Nikolus Austn nikolus.ustn@s..t Dpt. o Computr Sins Univrsity o Slzur http://rsrh.uni-slzur.t 1 Binry Brnh Distn Binry Rprsnttion o Tr Binry Brnhs Lowr Boun or

More information

Module 2 Motion Instructions

Module 2 Motion Instructions Moul 2 Motion Instrutions CAUTION: Bor you strt this xprimnt, unrstn tht you r xpt to ollow irtions EXPLICITLY! Tk your tim n r th irtions or h stp n or h prt o th xprimnt. You will rquir to ntr t in prtiulr

More information

Register Allocation. How to assign variables to finitely many registers? What to do when it can t be done? How to do so efficiently?

Register Allocation. How to assign variables to finitely many registers? What to do when it can t be done? How to do so efficiently? Rgistr Allotion Rgistr Allotion How to ssign vrils to initly mny rgistrs? Wht to o whn it n t on? How to o so iintly? Mony, Jun 3, 13 Mmory Wll Disprity twn CPU sp n mmory ss sp improvmnt Mony, Jun 3,

More information

Similarity Search. The Binary Branch Distance. Nikolaus Augsten.

Similarity Search. The Binary Branch Distance. Nikolaus Augsten. Similrity Srh Th Binry Brnh Distn Nikolus Augstn nikolus.ugstn@sg..t Dpt. of Computr Sins Univrsity of Slzurg http://rsrh.uni-slzurg.t Vrsion Jnury 11, 2017 Wintrsmstr 2016/2017 Augstn (Univ. Slzurg) Similrity

More information

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms rp loritms lrnin ojtivs loritms your sotwr systm sotwr rwr lrn wt rps r in mtmtil trms lrn ow to rprsnt rps in omputrs lrn out typil rp loritms wy rps? intuitivly, rp is orm y vrtis n s twn vrtis rps r

More information

Page 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S.

Page 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S. ConTst Clikr ustions Chtr 19 Physis, 4 th Eition Jms S. Wlkr ustion 19.1 Two hrg blls r rlling h othr s thy hng from th iling. Wht n you sy bout thir hrgs? Eltri Chrg I on is ositiv, th othr is ngtiv both

More information

ECE 407 Computer Aided Design for Electronic Systems. Circuit Modeling and Basic Graph Concepts/Algorithms. Instructor: Maria K. Michael.

ECE 407 Computer Aided Design for Electronic Systems. Circuit Modeling and Basic Graph Concepts/Algorithms. Instructor: Maria K. Michael. 0 Computr i Dsign or Eltroni Systms Ciruit Moling n si Grph Conptslgorithms Instrutor: Mri K. Mihl MKM - Ovrviw hviorl vs. Struturl mols Extrnl vs. Intrnl rprsnttions Funtionl moling t Logi lvl Struturl

More information

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals Intgrtion Continud Intgrtion y Prts Solving Dinit Intgrls: Ar Undr Curv Impropr Intgrls Intgrtion y Prts Prticulrly usul whn you r trying to tk th intgrl o som unction tht is th product o n lgric prssion

More information

A Low Noise and Reliable CMOS I/O Buffer for Mixed Low Voltage Applications

A Low Noise and Reliable CMOS I/O Buffer for Mixed Low Voltage Applications Proings of th 6th WSEAS Intrntionl Confrn on Miroltronis, Nnoltronis, Optoltronis, Istnul, Turky, My 27-29, 27 32 A Low Nois n Rlil CMOS I/O Buffr for Mix Low Voltg Applitions HWANG-CHERNG CHOW n YOU-GANG

More information

Problem solving by search

Problem solving by search Prolm solving y srh Tomáš voo Dprtmnt o Cyrntis, Vision or Roots n Autonomous ystms Mrh 5, 208 / 3 Outlin rh prolm. tt sp grphs. rh trs. trtgis, whih tr rnhs to hoos? trtgy/algorithm proprtis? Progrmming

More information

CS September 2018

CS September 2018 Loil los Distriut Systms 06. Loil los Assin squn numrs to msss All ooprtin prosss n r on orr o vnts vs. physil los: rport tim o y Assum no ntrl tim sour Eh systm mintins its own lol lo No totl orrin o

More information

Multipoint Alternate Marking method for passive and hybrid performance monitoring

Multipoint Alternate Marking method for passive and hybrid performance monitoring Multipoint Altrnt Mrkin mtho or pssiv n hyri prormn monitorin rt-iool-ippm-multipoint-lt-mrk-00 Pru, Jul 2017, IETF 99 Giuspp Fiool (Tlom Itli) Muro Coilio (Tlom Itli) Amo Spio (Politnio i Torino) Riro

More information

An Integer Linear Programming Based Routing Algorithm for Flip-Chip Design

An Integer Linear Programming Based Routing Algorithm for Flip-Chip Design . An Intgr Linr Progrmming Bs Routing Algorithm or Fli-Chi Dsign Ji-Wi Fng, Chin-Hsiung Hsu, n Yo-Wn Chng, Grut Institut o Eltronis Enginring, Ntionl Tiwn Univrsity, Tii 0, Tiwn Drtmnt o Eltril Enginring,

More information

Graphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari

Graphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari Grphs CSC 1300 Disrt Struturs Villnov Univrsity Grphs Grphs r isrt struturs onsis?ng of vr?s n gs tht onnt ths vr?s. Grphs n us to mol: omputr systms/ntworks mthm?l rl?ons logi iruit lyout jos/prosss f

More information

Solutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1

Solutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1 Solutions for HW Exris. () Us th rurrn rltion t(g) = t(g ) + t(g/) to ount th numr of spnning trs of v v v u u u Rmmr to kp multipl gs!! First rrw G so tht non of th gs ross: v u v Rursing on = (v, u ):

More information

Numbering Boundary Nodes

Numbering Boundary Nodes Numring Bounry Nos Lh MBri Empori Stt Univrsity August 10, 2001 1 Introution Th purpos of this ppr is to xplor how numring ltril rsistor ntworks ffts thir rspons mtrix, Λ. Morovr, wht n lrn from Λ out

More information

CS553 Lecture Register Allocation 1

CS553 Lecture Register Allocation 1 Low-Lvl Issus Lst ltur Livnss nlysis Rgistr llotion Toy Mor rgistr llotion Wnsy Common suxprssion limintion or PA2 Logistis PA1 is u PA2 hs n post Mony th 15 th, no lss u to LCPC in Orgon CS553 Ltur Rgistr

More information

MAT3707. Tutorial letter 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/201/1/2017

MAT3707. Tutorial letter 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/201/1/2017 MAT3707/201/1/2017 Tutoril lttr 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS MAT3707 Smstr 1 Dprtmnt o Mtmtil Sins SOLUTIONS TO ASSIGNMENT 01 BARCODE Din tomorrow. univrsity o sout ri SOLUTIONS TO ASSIGNMENT

More information

Computational Biology, Phylogenetic Trees. Consensus methods

Computational Biology, Phylogenetic Trees. Consensus methods Computtionl Biology, Phylognti Trs Consnsus mthos Asgr Bruun & Bo Simonsn Th 16th of Jnury 2008 Dprtmnt of Computr Sin Th univrsity of Copnhgn 0 Motivtion Givn olltion of Trs Τ = { T 0,..., T n } W wnt

More information

Solutions to Homework 5

Solutions to Homework 5 Solutions to Homwork 5 Pro. Silvia Frnánz Disrt Mathmatis Math 53A, Fall 2008. [3.4 #] (a) Thr ar x olor hois or vrtx an x or ah o th othr thr vrtis. So th hromati polynomial is P (G, x) =x (x ) 3. ()

More information

d e c b a d c b a d e c b a a c a d c c e b

d e c b a d c b a d e c b a a c a d c c e b FLAT PEYOTE STITCH Bin y mkin stoppr -- sw trou n pull it lon t tr until it is out 6 rom t n. Sw trou t in witout splittin t tr. You soul l to sli it up n own t tr ut it will sty in pl wn lt lon. Evn-Count

More information

Aquauno Video 6 Plus Page 1

Aquauno Video 6 Plus Page 1 Connt th timr to th tp. Aquuno Vio 6 Plus Pg 1 Usr mnul 3 lik! For Aquuno Vio 6 (p/n): 8456 For Aquuno Vio 6 Plus (p/n): 8413 Opn th timr unit y prssing th two uttons on th sis, n fit 9V lklin ttry. Whn

More information

Graph Contraction and Connectivity

Graph Contraction and Connectivity Chptr 17 Grph Contrtion n Conntivity So r w hv mostly ovr thniqus or solving prolms on grphs tht wr vlop in th ontxt o squntil lgorithms. Som o thm r sy to prllliz whil othrs r not. For xmpl, w sw tht

More information

temporally share the same FPGA Large circuit PI s micro-cycle one user cycle PO s

temporally share the same FPGA Large circuit PI s micro-cycle one user cycle PO s Ciruit Prtitioning for Dynmilly Rongurl FPGAs Huiqun Liu n D. F. Wong Dprtmnt of Computr Sins Unirsity of Txs t Austin Austin, T 787 Emil: fhqliu, wongg@s.utxs.u Astrt Dynmilly rongurl FPGAs h th potntil

More information

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees /1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our

More information

6202R. between SKY and GROUND. Statement sidewalk

6202R. between SKY and GROUND. Statement sidewalk twn SKY n GROUND Sttmnt siwlk wlkwy onnting rivrsi puli zons grnlin Lirris n musums in our tim r not only rsrv rtifts n ooks ut offr iffrnt vnts to visitors, host utionl n ivi progrms, nsur flxil sps for

More information

Jonathan Turner Exam 2-10/28/03

Jonathan Turner Exam 2-10/28/03 CS Algorihm n Progrm Prolm Exm Soluion S Soluion Jonhn Turnr Exm //. ( poin) In h Fioni hp ruur, u wn vrx u n i prn v u ing u v i v h lry lo hil in i l m hil o om ohr vrx. Suppo w hng hi, o h ing u i prorm

More information

Outline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem)

Outline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem) 4/25/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 2 Eulr s rig prolm

More information

CS61B Lecture #33. Administrivia: Autograder will run this evening. Today s Readings: Graph Structures: DSIJ, Chapter 12

CS61B Lecture #33. Administrivia: Autograder will run this evening. Today s Readings: Graph Structures: DSIJ, Chapter 12 Aministrivi: CS61B Ltur #33 Autogrr will run this vning. Toy s Rings: Grph Struturs: DSIJ, Chptr 12 Lst moifi: W Nov 8 00:39:28 2017 CS61B: Ltur #33 1 Why Grphs? For xprssing non-hirrhilly rlt itms Exmpls:

More information

CS200: Graphs. Graphs. Directed Graphs. Graphs/Networks Around Us. What can this represent? Sometimes we want to represent directionality:

CS200: Graphs. Graphs. Directed Graphs. Graphs/Networks Around Us. What can this represent? Sometimes we want to represent directionality: CS2: Grphs Prihr Ch. 4 Rosn Ch. Grphs A olltion of nos n gs Wht n this rprsnt? n A omputr ntwork n Astrtion of mp n Soil ntwork CS2 - Hsh Tls 2 Dirt Grphs Grphs/Ntworks Aroun Us A olltion of nos n irt

More information

A PROPOSAL OF FE MODELING OF UNIDIRECTIONAL COMPOSITE CONSIDERING UNCERTAIN MICRO STRUCTURE

A PROPOSAL OF FE MODELING OF UNIDIRECTIONAL COMPOSITE CONSIDERING UNCERTAIN MICRO STRUCTURE 18 TH INTERNATIONAL CONFERENCE ON COMPOSITE MATERIALS A PROPOSAL OF FE MODELING OF UNIDIRECTIONAL COMPOSITE CONSIDERING UNCERTAIN MICRO STRUCTURE Y.Fujit 1*, T. Kurshii 1, H.Ymtsu 1, M. Zo 2 1 Dpt. o Mngmnt

More information

Decimals DECIMALS.

Decimals DECIMALS. Dimls DECIMALS www.mthltis.o.uk ow os it work? Solutions Dimls P qustions Pl vlu o imls 0 000 00 000 0 000 00 0 000 00 0 000 00 0 000 tnths or 0 thousnths or 000 hunrths or 00 hunrths or 00 0 tn thousnths

More information

A 4-state solution to the Firing Squad Synchronization Problem based on hybrid rule 60 and 102 cellular automata

A 4-state solution to the Firing Squad Synchronization Problem based on hybrid rule 60 and 102 cellular automata A 4-stt solution to th Firing Squ Synhroniztion Prolm s on hyri rul 60 n 102 llulr utomt LI Ning 1, LIANG Shi-li 1*, CUI Shung 1, XU Mi-ling 1, ZHANG Ling 2 (1. Dprtmnt o Physis, Northst Norml Univrsity,

More information

Section 10.4 Connectivity (up to paths and isomorphism, not including)

Section 10.4 Connectivity (up to paths and isomorphism, not including) Toy w will isuss two stions: Stion 10.3 Rprsnting Grphs n Grph Isomorphism Stion 10.4 Conntivity (up to pths n isomorphism, not inluing) 1 10.3 Rprsnting Grphs n Grph Isomorphism Whn w r working on n lgorithm

More information

Layout Decomposition for Quadruple Patterning Lithography and Beyond

Layout Decomposition for Quadruple Patterning Lithography and Beyond Lyout Domposition for Qurupl Pttrning Lithogrphy n Byon Bi Yu ECE Dprtmnt Univrsity of Txs t Austin, Austin, TX i@r.utxs.u Dvi Z. Pn ECE Dprtmnt Univrsity of Txs t Austin, Austin, TX pn@.utxs.u ABSTRACT

More information

RAM Model. I/O Model. Real Machine Example: Nehalem : Algorithms in the Real World 4/9/13

RAM Model. I/O Model. Real Machine Example: Nehalem : Algorithms in the Real World 4/9/13 4//3 RAM Mol 5-853: Algorithms in th Rl Worl Lolity I: Ch-wr lgorithms Introution Sorting List rnking B-trs Bur trs Stnr thortil mol or nlyzing lgorithms: Ininit mmory siz Uniorm ss ost Evlut n lgorithm

More information

Announcements. Not graphs. These are Graphs. Applications of Graphs. Graph Definitions. Graphs & Graph Algorithms. A6 released today: Risk

Announcements. Not graphs. These are Graphs. Applications of Graphs. Graph Definitions. Graphs & Graph Algorithms. A6 released today: Risk Grphs & Grph Algorithms Ltur CS Spring 6 Announmnts A6 rls toy: Risk Strt signing with your prtnr sp Prlim usy Not grphs hs r Grphs K 5 K, =...not th kin w mn, nywy Applitions o Grphs Communition ntworks

More information

Greedy Algorithms, Activity Selection, Minimum Spanning Trees Scribes: Logan Short (2015), Virginia Date: May 18, 2016

Greedy Algorithms, Activity Selection, Minimum Spanning Trees Scribes: Logan Short (2015), Virginia Date: May 18, 2016 Ltur 4 Gry Algorithms, Ativity Sltion, Minimum Spnning Trs Sris: Logn Short (5), Virgini Dt: My, Gry Algorithms Suppos w wnt to solv prolm, n w r l to om up with som rursiv ormultion o th prolm tht woul

More information

Tangram Fractions Overview: Students will analyze standard and nonstandard

Tangram Fractions Overview: Students will analyze standard and nonstandard ACTIVITY 1 Mtrils: Stunt opis o tnrm mstrs trnsprnis o tnrm mstrs sissors PROCEDURE Skills: Dsriin n nmin polyons Stuyin onrun Comprin rtions Tnrm Frtions Ovrviw: Stunts will nlyz stnr n nonstnr tnrms

More information

DETAIL B DETAIL A 7 8 APPLY PRODUCT ID LABEL SB838XXXX ADJ FOUR POST RACK SQUARE HOLE RAIL B REVISION

DETAIL B DETAIL A 7 8 APPLY PRODUCT ID LABEL SB838XXXX ADJ FOUR POST RACK SQUARE HOLE RAIL B REVISION RVISION RV SRIPTION Y T HNG NO NOT OR PROUT LL JJH // LR TIL PPLY PROUT I LL TIL INSI UPPR ROSS MMR ON PR RK IS J OUR POST RK SQUR HOL RIL IS MN MS G NUT, PNL RNG 99 PPLY PROUT I LL INSI UPPR ROSS MMR

More information

C-201 Sheet Bar Measures 1 inch

C-201 Sheet Bar Measures 1 inch Janine M. lexander, P.. P.. No. 9, L 0 N. PRK RO, SUIT 0 HOLLYWOO, LORI 0 PHON: (9) - X: (9) 08- No.: 9 I ST SRIPTION Y GT VLVS SHLL RSILINT ST, MNUTUR TO MT OR X TH RQUIRMNTS O WW 09 (LTST RVISION) N

More information

Chem 104A, Fall 2016, Midterm 1 Key

Chem 104A, Fall 2016, Midterm 1 Key hm 104A, ll 2016, Mitrm 1 Ky 1) onstruct microstt tl for p 4 configurtion. Pls numrt th ms n ml for ch lctron in ch microstt in th tl. (Us th formt ml m s. Tht is spin -½ lctron in n s oritl woul writtn

More information

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES EZ SERVO EZSV17 WIRING DIAGRAM FOR BLDC MOTOR

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES EZ SERVO EZSV17 WIRING DIAGRAM FOR BLDC MOTOR 0V TO 0V SUPPLY GROUN +0V TO +0V RS85 ONVRTR 9 TO OM PORT ON P TO P OM PORT US 9600 U 8IT, NO PRITY, STOP, NO FLOW TRL. OPTO SNSOR # GROUN +0V TO +0V GROUN RS85 RS85 OPTO SNSOR # PHOTO TRNSISTOR TO OTHR

More information

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am 16.unii Introution to Computrs n Prormmin SOLUTIONS to Exmintion /30/0 9:05m - 10:00m Pro. I. Kristin Lunqvist Sprin 00 Grin Stion: Qustion 1 (5) Qustion (15) Qustion 3 (10) Qustion (35) Qustion 5 (10)

More information

Trees as operads. Lecture A formalism of trees

Trees as operads. Lecture A formalism of trees Ltur 2 rs s oprs In this ltur, w introu onvnint tgoris o trs tht will us or th inition o nroil sts. hs tgoris r gnrliztions o th simpliil tgory us to in simpliil sts. First w onsir th s o plnr trs n thn

More information

BASIC CAGE DETAILS SHOWN 3D MODEL: PSM ASY INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY SPRING FINGERS CLOSED TOP

BASIC CAGE DETAILS SHOWN 3D MODEL: PSM ASY INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY SPRING FINGERS CLOSED TOP MO: PSM SY SI TIS SOWN SPRIN INRS OS TOP INNR W TS R OIN OVR S N OVR OR RIIITY. R TURS US WIT OPTION T SINS. R (UNOMPRSS) RR S OPTION (S T ON ST ) IMNSIONS O INNR SIN TO UNTION WIT QU SM ORM-TOR (zqsp+)

More information

THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM. Texas Agricultural Experiment Station, Nueces County, 2000

THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM. Texas Agricultural Experiment Station, Nueces County, 2000 THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM Txs Agriulturl Exprimnt Sttion, Nus County, 2000 Roy D. Prkr Extnsion Entomologist Corpus Cristi, Txs SUMMARY: Grnug, yllow

More information

Weighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths

Weighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths Dt Strutur LECTURE Shortt pth lgorithm Proprti of hortt pth Bllmn-For lgorithm Dijktr lgorithm Chptr in th txtook (pp ). Wight grph -- rminr A wight grph i grph in whih g hv wight (ot) w(v i, v j ) >.

More information