Energy/Performance Design of Memory Hierarchies for Processor-in-Memory Chips

Size: px
Start display at page:

Download "Energy/Performance Design of Memory Hierarchies for Processor-in-Memory Chips"

Transcription

1 Energy/Performnce Design of Memory Hierrchies for Processor-in-Memory Chips Michel Hung, Jose Renu, Seung-Moon Yoo, Josep Torrells Deprmen of Compuer Science Deprmen of Elecricl n Compuer Engineering Universiy of Illinois Urbn-Chmpign hp://icom.cs.uiuc.eu/flexrm Inroucion Merging processors n memory ino single chip hs he well-known benefis of llowing high-bnwih n low-lency communicion beween processor n memory, n reucing energy consumpion. As resul, mny ifferen sysems bse on wh hs been clle Processor In Memory (PIM) rchiecures hve been propose [, 3, 7, 8,, 2 6, 8]. Recen vnces in echnology [, ] pper o mke i possible o inegre logic h cycles nerly s fs s in logic-only chip. As resul, processors re likely o pu much pressure on he relively slow on-chip DRAM. To hnle he spee mismch beween processors n DRAM, hese chips re likely o inclue non-rivil memory hierrchies in ech DRAM bnk. Wih mny on-chip high-frequency processors, ll of hem poenilly ccessing he memory sysem concurrenly, hese chips will consume much energy. In iion, hese chips re likely o be use in non-riionl plces like he memory of server [3, 7, 2] or he I/O subsysem [], which my no hve hevy-uy cooling suppor. Consequenly, i is imporn o esign he chips for energy efficiency. In his bsrc, we exmine, from performnce n energy-efficiency poin of view, he esign of he memory hierrchy in muli-bnke PIM chip wih mny simple, fs processors. Our resuls sugges he use of per-processor memory hierrchies h inclue moes-size cches, simple DRAM bnk orgnizions h suppor segmenion, n no prefeching. 2 Memory Hierrchies for PIM Chips Our focus rchiecure is PIM chip h inclues ens of relively simple, highfrequency processors, ech of which is ssocie wih bnk of DRAM. Such esign hs been suggese for sysems like Acive Pges [2, 3], FlexRAM [7], n DIVA [3] mong ohers. The chip cn be moele s in Figure -(), where he orgnizion of he This work ws suppore in pr by he Nionl Science Founion uner grns NSF Young Invesigor Awr MIP-9736, MIP-9693, n CCR-99788, DARPA Conrc DABT63-9-C-97, n gifs from IBM n Inel.

2 processors, memory, n nework my vry. We feel, however, h currenly-propose esigns re relively conservive in logic spee. Recen vnces in echnology pper o llow logic o cycle nerly s fs s in logic-only chip [, ]. This mens h hese chips my soon inclue processors cycling bou 8- MHz. Such processors re likely o pu much pressure on he slower DRAM. Processor Nework DRAM Bnk () Processor SRAM I-Mem D-Cche Sub-bnke DRAM (b) DB RB RB RB RB RB RB D Buffer Row Dec Row Dec Row Dec Row Dec D-Cche 26 DRAM 26 (c) Fig.. Exmple of chip rchiecure consiere. RB, DB, n Row Dec sn for row buffer, buffer n row ecoer, respecively. To hnle he spee mismch beween processors n DRAM, hese chips re likely o ssocie non-rivil memory hierrchy o ech DRAM bnk. In his pper, we ssume per-bnk bseline memory hierrchy s in Figure -(b). In he figure, he insrucion memory hierrchy inclues fs SRAM memory. The memory hierrchy inclues cche wih hrwre sequenil prefech of line. The DRAM bnk iself is sub-bnke n hs row n buffers. For exmple, Figure -(c) shows he DRAM orgnize ino 8 sub-bnks, wih row buffers, n 2 26-bi buffers. Unlike in memory-only chips, where he DRAM orgnizion is ofen limie o snr esigns, embee sysems llow mny ifferen orgnizions for he DRAM rry. For exmple, esigners cn chnge he wih n lengh of DRAM sub-bnk, n he number of sub-bnks. These chnges cn ffec he performnce elivere n he energy consume by DRAM ccesses, n he re uilize.

3 ) 876 : ;: In riionl DRAM rry orgnizion, when bnk is ccesse, every oher sub-bnk is cive. Consecuive sub-bnks re no cive becuse hey shre row buffer. Figure 2-() shows sub-bnk orgnizion. We now consier hree improvemens: segmenion, inerleving, n pipelining. 2 3!!!! Acive $ $ $ $ 2 % % % % $ % (,) (,) (,2) D Bus W Bi Line () Triionl (,) (,2) (,3) ;<<<< 2 3,- &' &' Acive ( () W,- 6 7././ = = W/2 = = 8 9 Acive (c) Inerleve Segmene (b) Segmene Wor Line : Aress Acivion Time : Sub-bnk Occupncy Time : D Trnsfer Time (x,y) y sub-bnk in bus x (,) (,) (,2) (,3) (,) (,) (,2) (,3) (,y) (2,y) (e) () Fig. 2. Differen DRAM bnk orgnizions n imings. Wih segmenion (Figure 2-(b)), only one sub-bnk is cive ime. The resuling row buffer ecoupling chnges he hi re of he row buffers. In iion, DRAM ccesses consume less energy: becuse only hlf of he bi lines re cive, bou % of he energy is sve. Wih inerleving, ech sub-bnk is vericlly slice n bus is ssigne o ech of he resuling slices. Figure 2-(c) shows 2-wy inerleve sysem. The performnce is higher becuse boh busses work in prllel (Figure 2-() shows iming igrm wih he mximum overlp, ssuming single ress bus). As for energy, lhough row buffer his now cos bi more, DRAM ccesses gin sve bou % of he energy becuse only hlf of he cells re cive. The re use increses. Finlly, one problem shown in Figure 2-() is h res from ifferen sub-bnks h shre bus re serilize by long sub-bnk occupncy imes. Wih pipelining, hese sub-bnks cn overlp heir occupncy imes (Figure 2-(e)). The only serilizion hppens in he shre ress bus n bus. The resul is higher performnce. As for energy, pipelining hs only smll impc. 3 Evluion Environmen We evlue he PIM chip of Secion 2 using MINT-bse simulion sysem [9]. The rchiecure moele is single chip wih 6 processors connece in ring. Ech processor is ssocie wih -Mbye DRAM bnk like in Figure -(b). The bseline

4 prmeers of ech processor-bnk pir re shown in Tble. The rge echnology is IBM m Blue Logic SA-27E ASIC [] wih he eful volge of.8 V. Processor D-Cche I-Memory D Buffer Row Buffer Sub-Bnk 2-issue in-orer 8MHz Sz: 8KB, WB Size: Kins. Number: Number: Number: BR Penly: 2 cycles Assoc: 2 Line: ins. Size: 26 b Size: KB Cols: 96 In,L/S,FP Unis: 2,, Line: 32 B RTrip:.2ns Bus: 26 b Bus: 26 b Rows: 2 Pening L,S: 2,2 RTrip:.2ns RTrip:3.7ns RTrip:7.ns RTrip: ns Tble. Prmeers for single memory bnk n processor pir. In he ble, BR n RTrip sn for brnch n conenion-free roun-rip lency from he processor, respecively. Appl. Wh I Does Problem Size D-Cche Averge Hi Re Power(W) GTree D mining: ree generion MB bse, 77.9 K recors, 29 ribues/recor.7.2 DTree D mining: ree eploymen. MB bse, 7. K recors, 29 ribues/recor BSOM BSOM neurl nework 2 K enries, ims, 2 iers, 6-noe nework, 832 KB b.97. BLAST BLAST proein mching 2.3 K sequences,. MB ol, query of 37 byes Mpeg MPEG-2 moion esimion 2x26 frme plus reference frme. Tol 2 KB FIC Frcl imge compressor 2x2 imge, 2x2 inernl srucure. Tol 2 MB Tble 2. Applicions execue. The nmes for he DRAM bnk orgnizions h we evlue re Tr, S, SP, IS, n ISP, which refer o riionl, segmene, segmene pipeline, inerleve segmene, ACBEDGFIH n inerleve segmene pipeline, respecively. In ech cse, we o refer o B -wys inerleve wih F sub-bnks per wy. To esime he energy consume in he chip, we hve pplie scling-own heory o on exising evices repore in he lierure, s well s use severl echniques n formuls repore in he lierure [6, 7, 9, 2]. We he conribuions of he processors, clock, memory hierrchies, n oher moules. A eile iscussion of he mehos h we hve followe cn be foun in [2]. In [2], we hve iionlly vlie our esimes wih CACTI [9] n wih publishe resuls on he ARM processor []. For he experimens, we use 6 pplicions h re suible o he ineger-bse PIM chip consiere: hey ccess lrge memory size, re very prllel, n re ineger bse. They come from severl inusril sources. We hve prllelize ech pplicion ino 6 hres by hn. Tble 2 liss he pplicions n heir chrcerisics. They inclue he omins of mining, neurl neworks, proein mching, mulimei, n imge compression. Ech pplicion runs for severl billions of insrucions.

5 Evluion The bes memory hierrchy orgnizion epens on he meric being opimize. We consier wo merics: performnce n energy-ely prouc. In our evluion, we sr wih he bseline rchiecure of Secion 3 n hen vry i. As reference, we use n iel rchiecure (Perf): los n sores re sisfie wih zero lency n consume no energy in he memory sysem. IPC Averge BLAST BSOM DTree FIC GTree Mpeg Tr(,) S(,) SP(,) IS(2,) ISP(2,) IS(2,8) ISP(2,8) Perf () Tr(,) S(,) SP(,) IS(2,) ISP(2,) IS(2,8) ISP(2,8) Perf (b) Fig. 3. Effec of he DRAM bnk orgnizion on he IPC in sysems wih -Kbye () n 8- Kbye (b) cches. Mximizing Performnce To compre performnce, we mesure he verge IPC elivere by he combine 6 processors for he urion of he pplicion. We firs evlue he effec of he memory bnk orgnizion. Figure 3 shows he IPC of he pplicions running on he bseline rchiecure for ifferen memory bnk orgnizions. Chrs () n (b) correspon o sysems wih - n 8-Kbye D-cches, respecively. The memory orgnizions re orere from he simpler ones on he lef sie o he more sophisice ones on he righ sie. Ech chr hs n Averge line h rcks he verge of ll pplicions. Figure 3-() shows h performnce improves slighly s we move o he more sophisice esigns. Going from Tr(,) o ISP(2,8) increses he IPC by n verge of 8%. However, for 8-Kbye cches (Figure 3-(b)), he chnges re very smll. This is becuse, wih lrge cches, here re relively few cche misses n, s resul, he ype of DRAM bnk orgnizion mers less. Compring he IPC in Perf n ISP(2,8), we see he IPC los in he mos vnce memory sysem. This frcion is on verge 8% n % in Figures 3-() n (b). Figure -() shows he effec of he cche size n prefeching suppor. We consier he bseline rchiecure wih hree ifferen DRAM bnk orgnizions: conservive (Tr(,)), ggressive (ISP(2,8)), n in-beween (IS(2,)). The figure shows he IPC verge over ll pplicions. We nlyze cches of 26 byes, Kbye, 8 Kbyes, n 6 Kbyes, ll wih n wihou prefeching. For ech memory orgnizion, here re 8 brs, lbele wih he cche size in byes followe by P or NP for prefeching or no prefeching, respecively.

6 The bes performnce is chieve wih he lrges cche size (6 Kbyes). However, lrge cches eliver iminishing reurns. The figure lso shows h ing he simple prefeching suppor consiere here mkes lile ifference o performnce. Energy-Dely Prouc Averge BLAST BSOM DTree FIC GTree Mpeg 2 2 Tr(,) S(,) SP(,) IS(2,) ISP(2,) IS(2,8) ISP(2,8) Perf Tr(,) S(,) SP(,) IS(2,) ISP(2,) IS(2,8) ISP(2,8) Perf () (b) Fig.. Effec of he DRAM bnk orgnizion on he energy-ely prouc in sysems wih - Kbye () n 8-Kbye (b) cches. Minimizing he Energy-Dely Prouc In embee sysems, common figure of meri is he energy-ely prouc [2]. A low prouc implies h he sysem is boh fs n energy-efficien. Consequenly, in his secion, we compre he energy-ely prouc of he chips wih ifferen memory hierrchy esigns. To compue he energy consume, we up he conribuions of ll he subsysems in he chip. Figures -() n -(b) show he energy-ely prouc of he chip uner he bseline rchiecure for ifferen DRAM bnk orgnizions. Chrs () n (b) correspon o sysems wih - n 8-Kbye D-cches respecively, n re orgnize s in Figures 3- () n 3-(b). For ech pplicion, he chrs re normlize o Perf. In sysems wih -Kbye cches (Figure -()), he verge energy-ely prouc ecreses for he more vnce memory orgnizions. For exmple, he prouc in ISP(2,8) is only 6% of h in Tr(,). The reson is h vnce DRAM bnk orgnizions eliver slighly higher IPCs n consume much less energy in he process. However, s cches increse o 8 Kbyes (Figure -(b)), he chnges re smller. Overll, for 8-Kbye cche sysems, only segmenion (going from Tr(,) o S(,)) mkes significn ifference. Supporing inerleving n incresing he number of sub-bnks from (2,) o (2,8) hs only smll effec. Figure -(b) mesures he energy-ely prouc for he verge of ll pplicions for ifferen cche sizes n prefeching suppor. The brs re normlize o Perf. From he figure, we see h esigns wih lrger cches en o hve lower energy-ely proucs. For exmple, in Tr(,), he prouc wih 6-Kbye cches is bou 3% of he prouc wih 26-bye cches. The reson is h cches hve ouble effec: hey spee up he progrm n, in iion, elimine energy-consuming memory ccesses. We observe, however, h for he more vnce memory orgnizions n lrge cches, he ren reverses: 6-Kbye cches re slighly worse hn 8-Kbye cches. The reson is

7 IPC NP 2NP 892NP 638NP 26P 2P 892P 638P 26NP 2NP 892NP 638NP 26P 2P 892P 638P 26NP 2NP Tr(,) IS(2,) ISP(2,8) () 892NP 638NP 26P 2P 892P 638P ED NP 2NP 892NP 638NP 26P 2P 892P 638P 26NP 2NP 892NP 638NP 26P 2P 892P 638P 26NP 2NP Tr(,) IS(2,) ISP(2,8) (b) 892NP 638NP 26P 2P 892P 638P Fig.. Effec of he cche size n prefeching suppor on IPC () n energy-ely prouc (b). h he iminishing reurns in lower miss res elivere by lrger cches o no compense for he higher energy consumpion h lrger cches require. We lso see h simple prefeching oes no help. Discussion In PIM chip like he one nlyze here, minimizing he energy-ely prouc is likely o be he op prioriy. Our resuls sugges o use moes-size D-cches (8 Kbyes), simple DRAM bnk orgnizion h suppors only segmenion, n no prefeching. Moes-size cches re effecive: hey spee-up he pplicion, re energy-efficien, consume moes re, n rener fncy DRAM bnk orgnizions lrgely unnecessry. If re is no n issue, he energy-ely prouc cn be improve slighly by supporing inerleving in he DRAM bnk n incresing he number of sub-bnks. References. A. Brown e l. ISTORE: Inrospecive Sorge for D-Inensive Nework Services. Workshop on Ho Topics in Opering Sysems, Mrch R. Gonzlez n M. Horowiz. Energy Dissipion In Generl Purpose Microprocessors. IEEE Journl on Soli-Se Circuis, 3():277 28, Sepember M. Hll e l. Mpping Irregulr Aplicions o DIVA, PIM-Bse D-Inensive Archiecure. In Supercompuing, November IBM Microelecronics. Blue Logic SA-27E ASIC. hp:// news/999/s27e, Februry S. Iyer n H. Kler. Embee DRAM Technology: Opporuniies n Chllenges. IEEE Specrum, April M. Kmble n K. Ghose. Anlyicl Energy Dissipion Moels for Low Power Cches. In Inernionl Symposium on Low Power Elecronics n Design, pges 3 8, Y. Kng, W. Hung, S. Yoo, D. Keen, Z. Ge, V. Lm, P. Pnik, n J. Torrells. FlexRAM: Towr n Avnce Inelligen Memory Sysem. In Inernionl Conference on Compuer Design, pges 92 2, Ocober 999.

8 8. P. Kogge, S. Bss, J. Brockmn, D. Chen, n E. Sh. Pursuing Peflop: Poin Designs for TF Compuers Using PIM Technologies. In Froniers of Mssively Prllel Compuion Symposium, V. Krishnn n J. Torrells. An Execuion-Driven Frmework for Fs n Accure Simulion of Supersclr Processors. In Inernionl Conference on Prllel Archiecures n Compilion Techniques, pges , Ocober K. Mi e l. Smr Memories: A Moulr Reconfigurble Archiecure. In Inernionl Symposium on Compuer Archiecure, June 2.. J. Monnro e l. A 6-MHz, 32-b,.-W CMOS RISC Microprocessor. IEEE Journl of Soli Se Circuis, 3():73 7, November M. Oskin, F. Chong, n T. Sherwoo. Acive Pges: A Compuion Moel for Inelligen Memory. In Inernionl Symposium on Compuer Archiecure, pges 92 23, June M. Oskin e l. Exploiing ILP in Pge-Bse Inelligen Memory. In Inernionl Symposium on Microrchiecure, D. Person e l. A Cse for Inelligen DRAM. IEEE Micro, pges 33, D. Person n M. Smih. Workshop on Mixing Logic n DRAM: Chips h Compue n Remember S. Rixner e l. A Bnwih-Efficien Archiecure for Mei Processing. In Inernionl Symposium on Microrchiecure, November C-L. Su n A. Despin. Cche Design Tre-offs for Power n Performnce Opimizion: A Cse Suy. In Inernionl Symposium on Low Power Elecronics n Design, pges 63 68, April E. Wingol e l. Bring I All o Sofwre: Rw Mchines. IEEE Compuer, pges 86 93, Sepember S. Wilon n N. Jouppi. CACTI: An Enhnce Cche Access n Cycle Time Moel. IEEE Journl on Soli-Se Circuis, 3(): , My N. Yeung e l. The Design of SPECin92 RISC Processor uner 2W. ISSCC Diges of Technicl Ppers, pges 26 27, Februry S-M. Yoo, J. Renu, M. Hung, n J. Torrells. FlexRAM Archiecure Design Prmeers. Technicl Repor CSRD-8, Deprmen of Compuer Science, Universiy of Illinois Urbn-Chmpign, Ocober 2. hp://icom.cs.uiuc.eu/flexrm/publicions.hml.

CS 314 Principles of Programming Languages

CS 314 Principles of Programming Languages CS 314 Principles of Progrmming Lnguges Lecure 10: Synx Direced Trnslion Zheng (Eddy) Zhng Rugers Universiy Februry 19, 2018 Clss Informion Homework 2 is sill being grded. Projec 1 nd homework 4 will be

More information

Grade 11 Physics Homework 3. Be prepared to defend your choices in class!

Grade 11 Physics Homework 3. Be prepared to defend your choices in class! Gre 11 Physics Homework 3 Be prepre o efen your choices in clss! 1. The grph shows he riion wih ime of he elociy of n objec. Which one of he following grphs bes represens he riion wih ime of he ccelerion

More information

Procedure Abstraction

Procedure Abstraction Compiler Design Procedure Absrcion Hwnsoo Hn Conrol Absrcion Procedures hve well-defined conrol-flow The Algol-60 procedure cll Invoked cll sie, wih some se of cul prmeers Conrol reurns o cll sie, immediely

More information

Today. Quiz Introduction to pipelining

Today. Quiz Introduction to pipelining Pipelining 1 Tody Quiz Inroduion o pipelining 2 Pipelining 10ns (10ns) 20ns (10ns) 30ns (10ns) Wh s he leny for one uni of work? Wh s he hroughpu? Pipelining 1.Brek up he logi wih lhes ino pipeline sges

More information

CL-Path in B-Spline Form with Global Error Control for 3-Axis Sculptured Surface Machining

CL-Path in B-Spline Form with Global Error Control for 3-Axis Sculptured Surface Machining n Inernionl onference on Mechnicl, Proucion n Auomobile Engineering (IMPAE'0) Singpore April 8-9, 0 -Ph in B-Spline Form wih Globl Error onrol for 3-Axis Sculpure Surfce Mchining Mqsoo Ahme. Khn, n Zezhong.

More information

Answer Key Lesson 6: Workshop: Angles and Lines

Answer Key Lesson 6: Workshop: Angles and Lines nswer Key esson 6: tudent Guide ngles nd ines Questions 1 3 (G p. 406) 1. 120 ; 360 2. hey re the sme. 3. 360 Here re four different ptterns tht re used to mke quilts. Work with your group. se your Power

More information

Stacking Tags in LLC Media

Stacking Tags in LLC Media Scking Tgs in LL Medi Normn Finn ugus 19, 2013 Ver. 2 (This presenion is lso uploded o 802.11 documen sysem s documen number 2013-0952-1.) bz-nfinn-ll-g-scking-0813-v01 IEEE 802.1 inerim meeing, Sep. 2013,

More information

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II

CS 152 Computer Architecture and Engineering. Lecture 7 - Memory Hierarchy-II CS 152 Compuer Archiecure and Engineering Lecure 7 - Memory Hierarchy-II Krse Asanovic Elecrical Engineering and Compuer Sciences Universiy of California a Berkeley hp://www.eecs.berkeley.edu/~krse hp://ins.eecs.berkeley.edu/~cs152

More information

Pipeline Example: Cycle 1. Pipeline Example: Cycle 2. Pipeline Example: Cycle 4. Pipeline Example: Cycle 3. 3 instructions. 3 instructions.

Pipeline Example: Cycle 1. Pipeline Example: Cycle 2. Pipeline Example: Cycle 4. Pipeline Example: Cycle 3. 3 instructions. 3 instructions. ipeline Exmple: Cycle 1 ipeline Exmple: Cycle X X/ /W X X/ /W $3,$,$1 lw $,0($5) $3,$,$1 3 instructions 8 9 ipeline Exmple: Cycle 3 ipeline Exmple: Cycle X X/ /W X X/ /W sw $6,($7) lw $,0($5) $3,$,$1 sw

More information

NEWTON S SECOND LAW OF MOTION

NEWTON S SECOND LAW OF MOTION Course and Secion Dae Names NEWTON S SECOND LAW OF MOTION The acceleraion of an objec is defined as he rae of change of elociy. If he elociy changes by an amoun in a ime, hen he aerage acceleraion during

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Optimal Crane Scheduling

Optimal Crane Scheduling Opimal Crane Scheduling Samid Hoda, John Hooker Laife Genc Kaya, Ben Peerson Carnegie Mellon Universiy Iiro Harjunkoski ABB Corporae Research EWO - 13 November 2007 1/16 Problem Track-mouned cranes move

More information

CS 152 Computer Architecture and Engineering. Lecture 6 - Memory

CS 152 Computer Architecture and Engineering. Lecture 6 - Memory CS 152 Compuer Archiecure and Engineering Lecure 6 - Memory Krse Asanovic Elecrical Engineering and Compuer Sciences Universiy of California a Berkeley hp://www.eecs.berkeley.edu/~krse hp://ins.eecs.berkeley.edu/~cs152

More information

Nearest-Neighbor and Fault-Tolerant Quantum Circuit Implementation

Nearest-Neighbor and Fault-Tolerant Quantum Circuit Implementation Neres-Neighbor nd Ful-olern Qunum Circui Implemenion Lxmidhr Biswl, Chndn Bndyopdhyy, Anupm Chopdhyy 2, Rober Wille 3, Rolf Drechsler 4, fizur Rhmn Indin Insiue of Engineering cience nd echnology hibpur,

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

This Unit: Processor Design. What Is Control? Example: Control for sw. Example: Control for add

This Unit: Processor Design. What Is Control? Example: Control for sw. Example: Control for add This Unit: rocessor Design Appliction O ompiler U ory Firmwre I/O Digitl ircuits Gtes & Trnsistors pth components n timing s n register files ories (RAMs) locking strtegies Mpping n IA to tpth ontrol Exceptions

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Caches I. CSE 351 Autumn Instructor: Justin Hsia

Caches I. CSE 351 Autumn Instructor: Justin Hsia L01: Intro, L01: L16: Combintionl Introduction Cches I Logic CSE369, CSE351, Autumn 2016 Cches I CSE 351 Autumn 2016 Instructor: Justin Hsi Teching Assistnts: Chris M Hunter Zhn John Kltenbch Kevin Bi

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS

FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS FIELD PROGRAMMABLE GATE ARRAY (FPGA) AS A NEW APPROACH TO IMPLEMENT THE CHAOTIC GENERATORS Mohammed A. Aseeri and M. I. Sobhy Deparmen of Elecronics, The Universiy of Ken a Canerbury Canerbury, Ken, CT2

More information

Assignment 2. Due Monday Feb. 12, 10:00pm.

Assignment 2. Due Monday Feb. 12, 10:00pm. Faculy of rs and Science Universiy of Torono CSC 358 - Inroducion o Compuer Neworks, Winer 218, LEC11 ssignmen 2 Due Monday Feb. 12, 1:pm. 1 Quesion 1 (2 Poins): Go-ack n RQ In his quesion, we review how

More information

Y. Tsiatouhas. VLSI Systems and Computer Architecture Lab

Y. Tsiatouhas. VLSI Systems and Computer Architecture Lab CMOS INEGRAED CIRCUI DESIGN ECHNIQUES Universiy of Ioannina Clocking Schemes Dep. of Compuer Science and Engineering Y. siaouhas CMOS Inegraed Circui Design echniques Overview 1. Jier Skew hroughpu Laency

More information

Chapter 2. 3/28/2004 H133 Spring

Chapter 2. 3/28/2004 H133 Spring Chpter 2 Newton believe tht light ws me up of smll prticles. This point ws ebte by scientists for mny yers n it ws not until the 1800 s when series of experiments emonstrte wve nture of light. (But be

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Lecture 10 Splines Introduction to Splines

Lecture 10 Splines Introduction to Splines ES8 Economerics. Inroducion o Splines. Esiming Spline Mehod One. Esiming Spline Mehod To.4 Cuic Splines Lecure Splines. Inroducion o Splines Firs pplied Poirier & Grer (974) in sud of profi res in hree

More information

Caches I. CSE 351 Spring Instructor: Ruth Anderson

Caches I. CSE 351 Spring Instructor: Ruth Anderson L16: Cches I Cches I CSE 351 Spring 2017 Instructor: Ruth Anderson Teching Assistnts: Dyln Johnson Kevin Bi Linxing Preston Jing Cody Ohlsen Yufng Sun Joshu Curtis L16: Cches I Administrivi Homework 3,

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Compiler-Assisted Cache Replacement

Compiler-Assisted Cache Replacement LCPC 3 Formulting The Prolem of Compiler-Assisted Cche Replcement Hongo Yng LCPC 3 Agend Bckground: Memory hierrchy, ISA with cche hints Prolem definition: How should compiler give cche hint to minimize

More information

File Manager Quick Reference Guide. June Prepared for the Mayo Clinic Enterprise Kahua Deployment

File Manager Quick Reference Guide. June Prepared for the Mayo Clinic Enterprise Kahua Deployment File Mnger Quick Reference Guide June 2018 Prepred for the Myo Clinic Enterprise Khu Deployment NVIGTION IN FILE MNGER To nvigte in File Mnger, users will mke use of the left pne to nvigte nd further pnes

More information

Implementing Ray Casting in Tetrahedral Meshes with Programmable Graphics Hardware (Technical Report)

Implementing Ray Casting in Tetrahedral Meshes with Programmable Graphics Hardware (Technical Report) Implemening Ray Casing in Terahedral Meshes wih Programmable Graphics Hardware (Technical Repor) Marin Kraus, Thomas Erl March 28, 2002 1 Inroducion Alhough cell-projecion, e.g., [3, 2], and resampling,

More information

A time-space consistency solution for hardware-in-the-loop simulation system

A time-space consistency solution for hardware-in-the-loop simulation system Inernaional Conference on Advanced Elecronic Science and Technology (AEST 206) A ime-space consisency soluion for hardware-in-he-loop simulaion sysem Zexin Jiang a Elecric Power Research Insiue of Guangdong

More information

3D Image Representation through Hierarchical Tensor Decomposition, Based on SVD with Elementary Tensor of size 2 2 2

3D Image Representation through Hierarchical Tensor Decomposition, Based on SVD with Elementary Tensor of size 2 2 2 WSEAS RASACIOS on SIGAL ROCESSIG Roumen Kouncev, Roumin Kouncev 3D Imge Represenion roug Hierrcicl ensor Decomposiion, Bse on SVD wi Elemenry ensor of size ROUME KOUCHEV Rio Communicions n Vieo ecnologies

More information

Parallel Square and Cube Computations

Parallel Square and Cube Computations Prllel Squre nd Cube Computtions Albert A. Liddicot nd Michel J. Flynn Computer Systems Lbortory, Deprtment of Electricl Engineering Stnford University Gtes Building 5 Serr Mll, Stnford, CA 945, USA liddicot@stnford.edu

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

DYNAMIC ROUTING ALGORITHMS IN VP-BASED ATM NETWORKS

DYNAMIC ROUTING ALGORITHMS IN VP-BASED ATM NETWORKS DYNAMIC ROUTING ALGORITHMS IN VP-BASED ATM NETWORKS Hon-Wi Chu n Dnny H K Tsng Deprtment of Electricl & Electronic Engineering The Hong Kong University of Science & Technology, Cler Wter By, Kowloon, Hong

More information

The Distributed Data Access Schemes in Lambda Grid Networks

The Distributed Data Access Schemes in Lambda Grid Networks The Distributed Dt Access Schemes in Lmbd Grid Networks Ryot Usui, Hiroyuki Miygi, Yutk Arkw, Storu Okmoto, nd Noki Ymnk Grdute School of Science for Open nd Environmentl Systems, Keio University, Jpn

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Engineer To Engineer Note

Engineer To Engineer Note Engineer To Engineer Note EE-186 Technicl Notes on using Anlog Devices' DSP components nd development tools Contct our technicl support by phone: (800) ANALOG-D or e-mil: dsp.support@nlog.com Or visit

More information

Caches I. CSE 351 Autumn 2018

Caches I. CSE 351 Autumn 2018 Cches I CSE 351 Autumn 2018 Instructors: Mx Willsey Luis Ceze Teching Assistnts: Britt Henderson Luks Joswik Josie Lee Wei Lin Dniel Snitkovsky Luis Veg Kory Wtson Ivy Yu Alt text: I looked t some of the

More information

STEREO PLANE MATCHING TECHNIQUE

STEREO PLANE MATCHING TECHNIQUE STEREO PLANE MATCHING TECHNIQUE Commission III KEY WORDS: Sereo Maching, Surface Modeling, Projecive Transformaion, Homography ABSTRACT: This paper presens a new ype of sereo maching algorihm called Sereo

More information

User Adjustable Process Scheduling Mechanism for a Multiprocessor Embedded System

User Adjustable Process Scheduling Mechanism for a Multiprocessor Embedded System Proceedings of he 6h WSEAS Inernaional Conference on Applied Compuer Science, Tenerife, Canary Islands, Spain, December 16-18, 2006 346 User Adjusable Process Scheduling Mechanism for a Muliprocessor Embedded

More information

Bruce McCarl's GAMS Newsletter Number 37

Bruce McCarl's GAMS Newsletter Number 37 Bruce McCrl's GAMS Newsletter Number 37 This newsletter covers 1 Uptes to Expne GAMS User Guie by McCrl et l.... 1 2 YouTube vieos... 1 3 Explntory text for tuple set elements... 1 4 Reing sets using GDXXRW...

More information

Sam knows that his MP3 player has 40% of its battery life left and that the battery charges by an additional 12 percentage points every 15 minutes.

Sam knows that his MP3 player has 40% of its battery life left and that the battery charges by an additional 12 percentage points every 15 minutes. 8.F Baery Charging Task Sam wans o ake his MP3 player and his video game player on a car rip. An hour before hey plan o leave, he realized ha he forgo o charge he baeries las nigh. A ha poin, he plugged

More information

Engineer To Engineer Note

Engineer To Engineer Note Engineer To Engineer Note EE-169 Technicl Notes on using Anlog Devices' DSP components nd development tools Contct our technicl support by phone: (800) ANALOG-D or e-mil: dsp.support@nlog.com Or visit

More information

PART 1 REFERENCE INFORMATION CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONITOR

PART 1 REFERENCE INFORMATION CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONITOR . ~ PART 1 c 0 \,).,,.,, REFERENCE NFORMATON CONTROL DATA 6400 SYSTEMS CENTRAL PROCESSOR MONTOR n CONTROL DATA 6400 Compuer Sysems, sysem funcions are normally handled by he Monior locaed in a Peripheral

More information

Jorge Salvador Marques, Stereo Reconstruction

Jorge Salvador Marques, Stereo Reconstruction Jorge Slvdor Mrques, Sereo Reconsrucion roblem Gol: reconsruc he D she of objecs in he scene from or more imges. Jorge Slvdor Mrques, Jorge Slvdor Mrques, secil cse f f f f b model reconsrucion, b - fb,

More information

In-HouseTrainingProgramme

In-HouseTrainingProgramme In-HouseTriningProgrmme Ocober2015-Mrch2015 KolkCluser MesgefromMr.DerekMichelShhEVP&Hed-MMHIC DerColegues Keepinginmindhecompe veenvironmenndlimiedopporuni esvilbleinhe presenmrkeiishigh meweriseoheoccsionndreinforceoursndofbeinghe

More information

12-B FRACTIONS AND DECIMALS

12-B FRACTIONS AND DECIMALS -B Frctions nd Decimls. () If ll four integers were negtive, their product would be positive, nd so could not equl one of them. If ll four integers were positive, their product would be much greter thn

More information

Overview. Making the Fast Case Common and the Uncommon Case Simple in Unbounded Transactional Memory. Running Example. Background

Overview. Making the Fast Case Common and the Uncommon Case Simple in Unbounded Transactional Memory. Running Example. Background Overview king the Fst Cse Common n the Uncommon Cse imple in Unoune Trnsctionl Colin Blunell (University of Pennsylvni) Joe Devietti (University of Pennsylvni) E Christopher Lewis (Vwre, Inc.) ilo. K.

More information

Dynamic Programming. Andreas Klappenecker. [partially based on slides by Prof. Welch] Monday, September 24, 2012

Dynamic Programming. Andreas Klappenecker. [partially based on slides by Prof. Welch] Monday, September 24, 2012 Dynmic Progrmming Andres Klppenecker [prtilly bsed on slides by Prof. Welch] 1 Dynmic Progrmming Optiml substructure An optiml solution to the problem contins within it optiml solutions to subproblems.

More information

CS 152 Computer Architecture and Engineering. Lecture 6 - Memory

CS 152 Computer Architecture and Engineering. Lecture 6 - Memory CS 152 Compuer Archiecure and Engineering Lecure 6 - Memory Krse Asanovic Elecrical Engineering and Compuer Sciences Universiy of California a Berkeley hp://www.eecs.berkeley.edu/~krse hp://ins.eecs.berkeley.edu/~cs152

More information

Shortest Path Algorithms. Lecture I: Shortest Path Algorithms. Example. Graphs and Matrices. Setting: Dr Kieran T. Herley.

Shortest Path Algorithms. Lecture I: Shortest Path Algorithms. Example. Graphs and Matrices. Setting: Dr Kieran T. Herley. Shores Pah Algorihms Background Seing: Lecure I: Shores Pah Algorihms Dr Kieran T. Herle Deparmen of Compuer Science Universi College Cork Ocober 201 direced graph, real edge weighs Le he lengh of a pah

More information

MATH 25 CLASS 5 NOTES, SEP

MATH 25 CLASS 5 NOTES, SEP MATH 25 CLASS 5 NOTES, SEP 30 2011 Contents 1. A brief diversion: reltively prime numbers 1 2. Lest common multiples 3 3. Finding ll solutions to x + by = c 4 Quick links to definitions/theorems Euclid

More information

Rule-Based Multi-Query Optimization

Rule-Based Multi-Query Optimization Rule-Based Muli-Query Opimizaion Mingsheng Hong Dep. of Compuer cience Cornell Universiy mshong@cs.cornell.edu Johannes Gehrke Dep. of Compuer cience Cornell Universiy johannes@cs.cornell.edu Mirek Riedewald

More information

A Routing Algorithm for Flip-Chip Design

A Routing Algorithm for Flip-Chip Design A Rouing Algorihm for Flip-hip Design Jia-Wei Fang, I-Jye Lin, and Yao-Wen hang, Graduae Insiue of Elecronics Engineering, Naional Taiwan Universiy, Taipei Deparmen of Elecrical Engineering, Naional Taiwan

More information

Gauss-Jordan Algorithm

Gauss-Jordan Algorithm Gauss-Jordan Algorihm The Gauss-Jordan algorihm is a sep by sep procedure for solving a sysem of linear equaions which may conain any number of variables and any number of equaions. The algorihm is carried

More information

MATH 2530: WORKSHEET 7. x 2 y dz dy dx =

MATH 2530: WORKSHEET 7. x 2 y dz dy dx = MATH 253: WORKSHT 7 () Wrm-up: () Review: polr coordintes, integrls involving polr coordintes, triple Riemnn sums, triple integrls, the pplictions of triple integrls (especilly to volume), nd cylindricl

More information

A Matching Algorithm for Content-Based Image Retrieval

A Matching Algorithm for Content-Based Image Retrieval A Maching Algorihm for Conen-Based Image Rerieval Sue J. Cho Deparmen of Compuer Science Seoul Naional Universiy Seoul, Korea Absrac Conen-based image rerieval sysem rerieves an image from a daabase using

More information

On the Detection of Step Edges in Algorithms Based on Gradient Vector Analysis

On the Detection of Step Edges in Algorithms Based on Gradient Vector Analysis On the Detection of Step Edges in Algorithms Bsed on Grdient Vector Anlysis A. Lrr6, E. Montseny Computer Engineering Dept. Universitt Rovir i Virgili Crreter de Slou sin 43006 Trrgon, Spin Emil: lrre@etse.urv.es

More information

CENG 477 Introduction to Computer Graphics. Modeling Transformations

CENG 477 Introduction to Computer Graphics. Modeling Transformations CENG 477 Inroducion o Compuer Graphics Modeling Transformaions Modeling Transformaions Model coordinaes o World coordinaes: Model coordinaes: All shapes wih heir local coordinaes and sies. world World

More information

NRMI: Natural and Efficient Middleware

NRMI: Natural and Efficient Middleware NRMI: Naural and Efficien Middleware Eli Tilevich and Yannis Smaragdakis Cener for Experimenal Research in Compuer Sysems (CERCS), College of Compuing, Georgia Tech {ilevich, yannis}@cc.gaech.edu Absrac

More information

Transparent neutral-element elimination in MPI reduction operations

Transparent neutral-element elimination in MPI reduction operations Trnsprent neutrl-element elimintion in MPI reduction opertions Jesper Lrsson Träff Deprtment of Scientific Computing University of Vienn Disclimer Exploiting repetition nd sprsity in input for reducing

More information

Research Article An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

Research Article An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing Hindawi Mobile Informaion Sysems Volume 2017, Aricle ID 9642958, 11 pages hps://doi.org/10.1155/2017/9642958 Research Aricle An Adapive and Inegraed Low-Power Framework for Mulicore Mobile Compuing Jongmoo

More information

9 Graph Cutting Procedures

9 Graph Cutting Procedures 9 Grph Cutting Procedures Lst clss we begn looking t how to embed rbitrry metrics into distributions of trees, nd proved the following theorem due to Brtl (1996): Theorem 9.1 (Brtl (1996)) Given metric

More information

Overview of Board Revisions

Overview of Board Revisions s Sysem Overview MicroAuoBox Embedded PC MicroAuoBox II can be enhanced wih he MicroAuoBox Embedded PC. The MicroAuoBox EmbeddedPC is powered via he MicroAuoBox II power inpu connecor. Wih he common power

More information

CEE598 - Visual Sensing for Civil Infrastructure Eng. & Mgmt.

CEE598 - Visual Sensing for Civil Infrastructure Eng. & Mgmt. CEE598 - Visul Sensing for Civil Infrsrucure Eng. & Mgm. Session 2 Review of Liner Algebr nd Geomeric Trnsformions Mni Golprvr-Frd Deprmen of Civil nd Environmenl Engineering Deprmen of Compuer Science

More information

Utility-Based Hybrid Memory Management

Utility-Based Hybrid Memory Management Uiliy-Based Hybrid Memory Managemen Yang Li Saugaa Ghose Jongmoo Choi Jin Sun Hui Wang Onur Mulu Carnegie Mellon Universiy Dankook Universiy Beihang Universiy ETH Zürich While he memory fooprins of cloud

More information

ECEN 468 Advanced Logic Design Lecture 36: RTL Optimization

ECEN 468 Advanced Logic Design Lecture 36: RTL Optimization ECEN 468 Advnced Logic Design Lecture 36: RTL Optimiztion ECEN 468 Lecture 36 RTL Design Optimiztions nd Trdeoffs 6.5 While creting dtpth during RTL design, there re severl optimiztions nd trdeoffs, involving

More information

3Applications Product code Page

3Applications Product code Page Single an win skin consrucion Auseniic sainless seel self rilling faseners Applicaions Prouc coe Page Shee o seel srucure / P. Shee o imber srucure Sie lap clamping W / SW2-S SW-A S2-S / SP2-S S2-A.8.11

More information

What do all those bits mean now? Number Systems and Arithmetic. Introduction to Binary Numbers. Questions About Numbers

What do all those bits mean now? Number Systems and Arithmetic. Introduction to Binary Numbers. Questions About Numbers Wht do ll those bits men now? bits (...) Number Systems nd Arithmetic or Computers go to elementry school instruction R-formt I-formt... integer dt number text chrs... floting point signed unsigned single

More information

COMP26120: Algorithms and Imperative Programming

COMP26120: Algorithms and Imperative Programming COMP26120 ecure C3 1/48 COMP26120: Algorihms and Imperaive Programming ecure C3: C - Recursive Daa Srucures Pee Jinks School of Compuer Science, Universiy of Mancheser Auumn 2011 COMP26120 ecure C3 2/48

More information

AML710 CAD LECTURE 11 SPACE CURVES. Space Curves Intrinsic properties Synthetic curves

AML710 CAD LECTURE 11 SPACE CURVES. Space Curves Intrinsic properties Synthetic curves AML7 CAD LECTURE Space Curves Inrinsic properies Synheic curves A curve which may pass hrough any region of hreedimensional space, as conrased o a plane curve which mus lie on a single plane. Space curves

More information

C 1. Last Time. CSE 490/590 Computer Architecture. Cache I. Branch Delay Slots (expose control hazard to software)

C 1. Last Time. CSE 490/590 Computer Architecture. Cache I. Branch Delay Slots (expose control hazard to software) CSE 490/590 Compuer Archiecure Cache I Seve Ko Compuer Sciences and Engineering Universiy a Buffalo Las Time Pipelining hazards Srucural hazards hazards Conrol hazards hazards Sall Bypass Conrol hazards

More information

CAMERA CALIBRATION BY REGISTRATION STEREO RECONSTRUCTION TO 3D MODEL

CAMERA CALIBRATION BY REGISTRATION STEREO RECONSTRUCTION TO 3D MODEL CAMERA CALIBRATION BY REGISTRATION STEREO RECONSTRUCTION TO 3D MODEL Klečka Jan Docoral Degree Programme (1), FEEC BUT E-mail: xkleck01@sud.feec.vubr.cz Supervised by: Horák Karel E-mail: horak@feec.vubr.cz

More information

3.5.1 Single slit diffraction

3.5.1 Single slit diffraction 3..1 Single slit diffrction ves pssing through single slit will lso diffrct nd produce n interference pttern. The reson for this is to do with the finite width of the slit. e will consider this lter. Tke

More information

ECE 468/573 Midterm 1 September 28, 2012

ECE 468/573 Midterm 1 September 28, 2012 ECE 468/573 Midterm 1 September 28, 2012 Nme:! Purdue emil:! Plese sign the following: I ffirm tht the nswers given on this test re mine nd mine lone. I did not receive help from ny person or mteril (other

More information

Mobility Support for a QoS Aggregation Protocol

Mobility Support for a QoS Aggregation Protocol Mobility Support for QoS Aggregtion Protocol A. Kloxylos^, D. Vli*, S. Psklis+, G. Pngiotou^, I. Goninkis^, E. Zervs # ^ Deprtment of Telecommunictions Science n Technology, University of Peloponnese,

More information

Chapter 4 Sequential Instructions

Chapter 4 Sequential Instructions Chaper 4 Sequenial Insrucions The sequenial insrucions of FBs-PLC shown in his chaper are also lised in secion 3.. Please refer o Chaper, "PLC Ladder diagram and he Coding rules of Mnemonic insrucion",

More information

pdfapilot Server 2 Manual

pdfapilot Server 2 Manual pdfpilot Server 2 Mnul 2011 by clls softwre gmbh Schönhuser Allee 6/7 D 10119 Berlin Germny info@cllssoftwre.com www.cllssoftwre.com Mnul clls pdfpilot Server 2 Pge 2 clls pdfpilot Server 2 Mnul Lst modified:

More information

In fmri a Dual Echo Time EPI Pulse Sequence Can Induce Sources of Error in Dynamic Magnetic Field Maps

In fmri a Dual Echo Time EPI Pulse Sequence Can Induce Sources of Error in Dynamic Magnetic Field Maps In fmri a Dual Echo Time EPI Pulse Sequence Can Induce Sources of Error in Dynamic Magneic Field Maps A. D. Hahn 1, A. S. Nencka 1 and D. B. Rowe 2,1 1 Medical College of Wisconsin, Milwaukee, WI, Unied

More information

Video Content Description Using Fuzzy Spatio-Temporal Relations

Video Content Description Using Fuzzy Spatio-Temporal Relations Proceedings of he 4s Hawaii Inernaional Conference on Sysem Sciences - 008 Video Conen Descripion Using Fuzzy Spaio-Temporal Relaions rchana M. Rajurkar *, R.C. Joshi and Sananu Chaudhary 3 Dep of Compuer

More information

Exchange Market Pressure and Monetary Policies

Exchange Market Pressure and Monetary Policies Avilble online www.econ.upm.edu.my GCBER 27 Augus 4-5, UPM, Mlysi Globl Conference on Business nd Economics Reserch Governnce nd Susinbiliy of Globl Business Economics Globl Conference on Business nd Economics

More information

Some necessary and sufficient conditions for two variable orthogonal designs in order 44

Some necessary and sufficient conditions for two variable orthogonal designs in order 44 University of Wollongong Reserch Online Fculty of Informtics - Ppers (Archive) Fculty of Engineering n Informtion Sciences 1998 Some necessry n sufficient conitions for two vrile orthogonl esigns in orer

More information

Guarding curvilinear art galleries with edge or mobile guards

Guarding curvilinear art galleries with edge or mobile guards Guaring curvilinear ar galleries wih ege or mobile guars Menelaos I. Karavelas Deparmen of Applie Mahemaics, Universiy of Cree, GR-1 09 Heraklion, Greece, an Insiue of Applie an Compuaional Mahemaics,

More information

Simple Network Management Based on PHP and SNMP

Simple Network Management Based on PHP and SNMP Simple Nework Managemen Based on PHP and SNMP Krasimir Trichkov, Elisavea Trichkova bsrac: This paper aims o presen simple mehod for nework managemen based on SNMP - managemen of Cisco rouer. The paper

More information

Coded Caching with Multiple File Requests

Coded Caching with Multiple File Requests Coded Caching wih Muliple File Requess Yi-Peng Wei Sennur Ulukus Deparmen of Elecrical and Compuer Engineering Universiy of Maryland College Park, MD 20742 ypwei@umd.edu ulukus@umd.edu Absrac We sudy a

More information

MIC2569. Features. General Description. Applications. Typical Application. CableCARD Power Switch

MIC2569. Features. General Description. Applications. Typical Application. CableCARD Power Switch CableCARD Power Swich General Descripion is designed o supply power o OpenCable sysems and CableCARD hoss. These CableCARDs are also known as Poin of Disribuion (POD) cards. suppors boh Single and Muliple

More information

Numerical Solution of ODE

Numerical Solution of ODE Numerical Soluion of ODE Euler and Implici Euler resar; wih(deools): wih(plos): The package ploools conains more funcions for ploing, especially a funcion o draw a single line: wih(ploools): wih(linearalgebra):

More information

INFORMATION SECURITY

INFORMATION SECURITY ISSN 2075-078. Science-Base Technologies 203. 2 (8) 79 INFORMATION SECRITY DC 629.39 THE METHOD OF TIME SPENT ESTIMATING ON PROCESSING AND TRANSMISSION OF COMPRESSED VIDEO STREAM A. Leah I. Cheremsoy 2

More information

II. THE ALGORITHM. A. Depth Map Processing

II. THE ALGORITHM. A. Depth Map Processing Lerning Plnr Geometric Scene Context Using Stereo Vision Pul G. Bumstrck, Bryn D. Brudevold, nd Pul D. Reynolds {pbumstrck,brynb,pulr2}@stnford.edu CS229 Finl Project Report December 15, 2006 Abstrct A

More information

Fill in the following table for the functions shown below.

Fill in the following table for the functions shown below. By: Carl H. Durney and Neil E. Coer Example 1 EX: Fill in he following able for he funcions shown below. he funcion is odd he funcion is even he funcion has shif-flip symmery he funcion has quarer-wave

More information

source managemen, naming, proecion, and service provisions. This paper concenraes on he basic processor scheduling aspecs of resource managemen. 2 The

source managemen, naming, proecion, and service provisions. This paper concenraes on he basic processor scheduling aspecs of resource managemen. 2 The Virual Compuers A New Paradigm for Disribued Operaing Sysems Banu Ozden y Aaron J. Goldberg Avi Silberschaz z 600 Mounain Ave. AT&T Bell Laboraories Murray Hill, NJ 07974 Absrac The virual compuers (VC)

More information

Lecture 18: Mix net Voting Systems

Lecture 18: Mix net Voting Systems 6.897: Advanced Topics in Crypography Apr 9, 2004 Lecure 18: Mix ne Voing Sysems Scribed by: Yael Tauman Kalai 1 Inroducion In he previous lecure, we defined he noion of an elecronic voing sysem, and specified

More information

Caches I. CSE 351 Autumn Instructor: Justin Hsia

Caches I. CSE 351 Autumn Instructor: Justin Hsia L16: Cches I Cches I CSE 351 Autumn 2017 Instructor: Justin Hsi Teching Assistnts: Lucs Wotton Michel Zhng Prker DeWilde Ryn Wong Sm Gehmn Sm Wolfson Svnn Yee Vinny Plnippn Alt text: I looked t some of

More information

RULES OF DIFFERENTIATION LESSON PLAN. C2 Topic Overview CALCULUS

RULES OF DIFFERENTIATION LESSON PLAN. C2 Topic Overview CALCULUS CALCULUS C Topic Overview C RULES OF DIFFERENTIATION In pracice we o no carry ou iffereniaion from fir principle (a ecribe in Topic C Inroucion o Differeniaion). Inea we ue a e of rule ha allow u o obain

More information

Location. Electrical. Loads. 2-wire mains-rated. 0.5 mm² to 1.5 mm² Max. length 300 m (with 1.5 mm² cable). Example: Belden 8471

Location. Electrical. Loads. 2-wire mains-rated. 0.5 mm² to 1.5 mm² Max. length 300 m (with 1.5 mm² cable). Example: Belden 8471 Produc Descripion Insallaion and User Guide Transiser Dimmer (454) The DIN rail mouned 454 is a 4channel ransisor dimmer. I can operae in one of wo modes; leading edge or railing edge. All 4 channels operae

More information

Parallel and Distributed Systems for Constructive Neural Network Learning*

Parallel and Distributed Systems for Constructive Neural Network Learning* Parallel and Disribued Sysems for Consrucive Neural Nework Learning* J. Flecher Z. Obradovi School of Elecrical Engineering and Compuer Science Washingon Sae Universiy Pullman WA 99164-2752 Absrac A consrucive

More information

Questions About Numbers. Number Systems and Arithmetic. Introduction to Binary Numbers. Negative Numbers?

Questions About Numbers. Number Systems and Arithmetic. Introduction to Binary Numbers. Negative Numbers? Questions About Numbers Number Systems nd Arithmetic or Computers go to elementry school How do you represent negtive numbers? frctions? relly lrge numbers? relly smll numbers? How do you do rithmetic?

More information

Doctoral Dissertation Proposal: Acceleration of Network Processing Algorithms

Doctoral Dissertation Proposal: Acceleration of Network Processing Algorithms Doctorl Disserttion Proposl: Accelertion of Network Processing Algorithms Silesh Kumr Wshington University Computer Science n Engineering St. Louis, MO 633-4899 +-34-935-436 silesh@rl.wustl.eu Reserch

More information