APPLICATION NOTE PACE1750AE BUILT-IN FUNCTIONS
|
|
- Erik Dean
- 5 years ago
- Views:
Transcription
1 APPLICATION NOTE PACE175AE BUILT-IN UNCTIONS About This Note This applicatio brief is iteded to explai ad demostrate the use of the special fuctios that are built ito the PACE175AE processor. These powerful Built-I uctios (BIs) are above ad beyod the capabilities of the MIL- STD-175A istructio set, but are allowed by MIL-STD-175A as optios to ehace the performace of 175A processors i specialized applicatios. The desig of the PACE175AE is based o its successful high-performace predecessor, the PACE175A, ad is i fact pi ad software compatible with that part. However, certai architectural ehacemets allow the PACE175AE to gai a percet throughput icrease over the PACE175A at ay give clock frequecy, up to MHz, as measured o the DAIS istructio mix. The most sigificat of these ehacemets is the additio of a multiply accumulate array capable of completig a sigle precisio iteger (16-bit x 16-bit) or sigle precisio floatig poit (2-bit x 2-bit) multiply accumulate operatio i just two clocks. Besides improvig the performace of the iteger ad floatig poit arithmetic by as much as 7 percet over the PACE175A, the multiply accumulate array gave the desigers of the PACE175AE a importat buildig block from which to create the very powerful BIs that are the subject of this ote. I additio to the fuctios which utilize the multiply accumulate array, there are fuctios which improve the usefuless of the A ad B timers, ad a block move i the I/O address space which greatly improves the speed at which the memory map ca be chaged. These fuctios combied ca offer a sigificat improvemet i the system performace of the PACE175AE processor family i may typical embedded applicatios. DSP uctios The P175AE device icorporates a series of fuctios, utilizig the multiply accumulate array, iteded to vastly improve performace o the operatios most used i digital sigal processig applicatios. With the additio of these fuctios, the P175AE is able to perform some of the basic DSP fuctios with speeds rivalig those of may of the dedicated DSP processors curretly available. All of these fuctios utilize iput data i sigle or double precisio iteger format ad provide results i a double precisio iteger format or i a special 8-bit iteger format for improved accuracy. These istructios may be used i a wide variety of applicatios, icludig IR filters, covolutio, correlatio ad matrix multiplicatio. A IR filter implemeted usig the VDPS will execute i 8 clocks per tap. or the commoly used 3 x 3 matrix operatios (graphics, coordiate trasformatio, Euler rotatios, etc.) a special register based BI is provided. It will compute a 3 x 3 colum/row multiplicatio i oly 6 clocks. Descriptios of each of these fuctios are provided i the followig paragraphs. I all cases, for calculatig the effects of wait states, WD is the umber of data wait states used ad WI is the umber of istructio wait states used. Revised October 25
2 PACE175AE BUILT-IN UNCTIONS Parametric Memory to Memory Vector Dot Product (16-bit data, 32-bit result) VDPS RA uctio: Acc( : 31) Acc( : 31) + i= 1 Mi( :15) Ni( :15) CPU Registers Memory RA RA + 1 RA + 2 = M1 M2 M N1 N2 N The VDPS istructio computes the vector dot product of two 16-bit memory arrays. The address of the first elemet of the first vector must be placed i register RA, the address of the first elemet of the secod vector must be placed i register RA+1 ad the umber of elemets i each vector () must be placed i register RA+2. Whe executio begis, each elemet of the first vector is multiplied with the correspodig elemet of the secod vector ad the 32- bit result added to the accumulator. Whe executio is complete, the value i RA+2 will have chaged to zero ad the result will be stored i the accumulator, which ca be accessed via the STAC commad, to be discussed later. Overflowig the accumulator will result i the ixed-poit Overflow iterrupt. 1 + (8 ) clocks ( wait states) lags Affected: (WI-6) + (WD 2) additioal clocks P, Z, N Page 2 of 15
3 PACE 175AE BUILT-IN UNCTIONS Parametric Memory to Memory Dot Product (32-bit data, 8-bit result) VDPD RA uctio: Acc( : 7) Acc( : 7) + i= 1 Mi( :31) Ni( :31) CPU Registers Memory RA RA + 1 RA + 2 = M1(:15) M1(16:31) M2(:15) M2(16:31) 2 M(:15) M(16:31) N1(:15) N1(16:31) N2(:15) N2(16:31) 2 N(:15) N(16:31) The VDPD istructio computes the vector dot product of two 32 bit memory arrays. The address of the first elemet of the first vector must be placed i register RA, the address of the first elemet of the secod i RA+1 ad the umber of elemets i each vector i RA+2. The 32 bit elemets must be placed i two adjacet memory locatios with the most sigificat 16 bits residig i the memory locatio with the lower address. Both vectors must reside withi the same address state (if a MMU is used). Whe executio is complete, the cotets of register RA+2 will be zero ad the result will be i the 8-bit accumulator. There will be o iterrupt geerated o a overflow. lags Affected: clocks (WI-6) + (WD ) additioal clocks Page 3 of 15
4 PACE175AE BUILT-IN UNCTIONS 3 X 3 Register Dot Product (16-bit data, 32-bit result) R3DP uctio: Acc ( : 31) Acc( : 31) + ( R R3) + ( R1 R) + ( R2 R5) R R1 R2 CPU Registers R3 R R5 The R3DP istructio computes the dot product of the two 16-bit 3-elemet vectors formed by registers R-R2 ad R3- R5. R-R2 cotai the elemets of the first vector ad R3-R5 cotai the elemets of the secod vector. The 32-bit result is placed i the accumulator. A overflow of the accumulator will cause a ixed-poit Overflow Iterrupt to occur. logs Affected: 6 clocks (WI-2) additioal clocks Page of 15
5 PACE 175AE BUILT-IN UNCTIONS Double Precisio Multiply/Accumulate (32-bit data, 8-bit result) MACD uctio: Acc ( : 7) Acc( : 7) + ( R, R1) ( R2, R3) CPU Registers R R1 R2 R3 The MACD istructio is the basic double precisio multiply ad accumulate fuctio. It performs a 32-bit multiply of the data i two register pairs, R-R1 ad R2-R3, ad adds the 8-bit result to the value i the accumulator. The most sigificat 16 bits of the data to be multiplied must be placed i R for the first operad ad R2 for the secod, ad the least sigificat 16 bits must be placed i R1 ad R3. A overflow of the accumulator will ot cause a iterrupt to the processor. 8 clocks (WI-) additioal clocks 1 lags 2 Affected: Page 5 of 15
6 PACE175AE BUILT-IN UNCTIONS Trascedetal uctios The P175AE implemets a polyomial evaluatio BI which may be used to evaluate ay fuctio which may be expressed as a series expasio. This icludes fuctios such as sie, cosie, atural log, ad may others. The use of the POLY BI results i a sigificat performace improvemet over the calculatio of these fuctios with idividual multiply ad add istructios. Polyomial POLY uctio: Acc( : 31) i= A X CPU Registers Memory R R1 R2 = x = A A-1 A-2 +1 A The POLY istructio evaluates the polyomial of degree defied by the registers ad memory as depicted above. The values of X ad the costats A -A are represeted as u-ormalized 16-bit two s complemet fractios providig a rage i value of -1<X<1. The most sigificat bit is a sig bit, ad the remaiig 15 bits represet the fixed poit fractio. The result is represeted as a u-ormalized 2-bit two s complemet fractio, providig icreased accuracy. The address of A must be placed i register R, the value of X must be placed i R1 ad the value of, the degree of the polyomial, must be placed i R2. The coefficiets of the polyomial must be placed i memory with A i the first address ad A -1 through A followig i ascedig addresses. A overflow of the accumulator will ot cause a iterrupt to the processor. lags Affected: 6(+1)+8 clocks (WD(+1))+WI additioal clocks Page 6 of 15
7 PACE 175AE BUILT-IN UNCTIONS Example: Usig the POLY to evaluate SIN X The POLY istructio leds itself well to the evaluatio of fuctios which may be expaded ito series represetatios. Oe such fuctio is si x, which may be expaded ito the Taylor Series represeted below with x equal to the value of a agle i radias: ( 1 ) si x = = ( 1) x x x x = x + + (2 + 1)! 3! 5! 7! 5 7 This may be reorgaized ito the followig equatio: 2 ( 2 ) si x = A + A x + A x + A x + A x + A x + A x + A x which is the format accepted by the POLY istructio. Sice the series is ifiite, with icreasig accuracy for each additioal term, the particular umber of terms required for a acceptable error must be determied. It ca be show that for -1<x<1, a error of less tha.2 percet may be achieved by usig just four of the terms of equatio (1), which is acceptable i most applicatios. It is actually ot possible to use ay more tha four terms for the sie calculatio usig the POLY istructio sice the ext costat required (1/9!) is too small i magitude to represet as a 16-bit fixed poit fractio. Thus, the followig equatio will be used to approximate the sie fuctio: ( 3 ) x x x si x = x + 3! 5! 7! A1 x + A2 x + A3 x + A x + A5 x + A6 x A7 x = A + where: A = A = A 1 = 1 = 7 (hex) A 5 = 1/5! = 111 (hex) A 2 = A 6 = A 3 = -1/3! = EAAA (hex) A 7 = -1/7! = A (hex) Sice the above costats may oly be etered as 16-bit fractios, some additioal error is itroduced, but the accuracy of the result is still very reasoable, as this example will show. To calculate the value of si x with x =.75 radias (2.97 ) the followig must be performed: 1. Place the costats i the memory. (I this example, address (hex) is chose as the startig address) Address Data Address Data A EAAA Page 7 of 15
8 PACE175AE BUILT-IN UNCTIONS 2. Execute the followig program: LIM R, ; Load startig address of costat table LIM R1, 6 ; Load the value of x (.75) LIM R2, 7 ; Load the value of POLY ; Execute the POLY istructio 3. The result is i the accumulator ad may be retrieved as described later i this ote. or this example, the result is 573E3 (hex) which traslates to decimal. The actual value of si.75 is , resultig i a error of. percet. I the example above, the POLY istructio executes i 56 clocks. If the same fuctio were performed usig idividual multiply ad add istructios with greater tha 16 bits of precisio, the calculatio would require double precisio iteger register multiplies (36 clocks), 1 sigle precisio iteger memory multiply with 32-bit product (13 clocks) ad 3 double precisio iteger memory additios (8 clocks) for a total of 97 clocks. Thus, the POLY istructio calculates the sie fuctio 2 percet faster tha the discrete istructios. If floatig poit accuracy is required, the floatig poit adds ad multiplies must be used. The limitatios o the value of x require that some preprocessig of the data be performed before the POLY is executed. or values of x greater tha 1, the relatioships show below ca be of help: si x = cos (x-π/2) cos x = -si (x-π/2) si x = si (x-2π) cos x = cos (x-2π) uctios other tha sie may be evaluated by the POLY as well. Ay fuctio which may be expaded ito a series may be evaluated, however, for suitable accuracy the series must coverge rather quickly. The series approximatig some importat fuctio are show below: cos x = = ( 1) 2 2 x x x x = (2)! 2!! 6! 6 e x = = x! 2 x x x = 1+ x ! 3!! 3 Page 8 of 15
9 PACE 175AE BUILT-IN UNCTIONS Accumulator Maipulatio The PACE175AE provides a group of istructios to allow complete access to the 8-bit accumulator used i the BIs described above. This provides the user the flexibility to use the multiply/accumulate array to supplemet the performace of may custom applicatios. These istructios are described below: Clear Accumulator CLAC uctio: Acc( : 7) The 8-bit accumulator is loaded with. No registers are affected. clocks lags affected: WI additioal clocks Store Accumulator ito R, R STA Op code: uctio: R, R1 Acc( : 31) The most sigificat 32 bits of the accumulator are placed i the R,R1 register pair. The most sigificat 16 bits are placed i R ad the least sigificat 16 bits are placed i R1. lags Affected: 7 clocks (WI 3) additioal clocks Page 9 of 15
10 PACE175AE BUILT-IN UNCTIONS Store Accumulator Log ito R,R1,R2 STAL Op Code: uctio: R, R1, R2 Acc( : 7) The 8-bit accumulator is placed i the three register group, R,R1,R2. The most sigificat 16 bits are placed i R, ad the least sigificat 16 bits are placed i R2. lags Affected: 1 clocks (WI 6) additioal clocks Load Accumulator LAC uctio: The most sigificat 32 bits of the accumulator are loaded with the data cotaied i the register pair R ad R1. The most sigificat 16 bits are loaded from R ad the least sigificat from R1. lags Affected: 1 clocks (WI 6) additioal clocks Page 1 of 15
11 PACE 175AE BUILT-IN UNCTIONS Load Accumulator Log LACL uctio: Acc( : 7) R, R1, R2 The 8-bit accumulator is loaded with the cotets of the register group R,R1,R2. The most sigificat 16 bits are loaded from R ad the least sigificat 16 bits are loaded from R2. lags Affected: 9 clocks (WI 5) additioal clocks Timers 1 The A ad B timers are specified by MIL-STD-175A as optios which are implemeted by the PACE175AE. These timers 2 are iteded 3 to provide 5 periodic 6 7iterrupts 8 to 9the applicatio 1 11 software 12 for 13real time 1 operatio. 15 The ca be loaded (via XIO istructios) with a value from which to cout upward util reachig the value (hex), at which time they 7 roll over to ad geerate a iterrupt to the processor. rom this poit they will cotiue coutig up toward (hex) agai, uless loaded with a differet value. Thus, if a periodic iterrupt is desired with a period of less tha 65,536 couts, the timer must be reloaded after each iterrupt with a cout value other tha zero. The PACE175AE cotais two additioal registers, called reset registers, which may cotai a value differet tha zero for the timers to cout up from after reachig their termial couts. This provides a very simple method of creatig periodic real time iterrupts with ay period. The user must simply program each register oce to set the iterrupt period, after which the iterrupts will occur regularly util a differet value is writte ito oe of the registers. These two registers default to zero upo power-up, meaig that if they are ever chaged, full compatibility with the software developed for the PACE175AE ad other machies is maitaied. The registers are loaded by the BIs described below, but caot be read. Page 11 of 15
12 PACE175AE BUILT-IN UNCTIONS Load Timer A Reset Register LTAR uctio: TAR R The Timer A Reset Register is loaded with the value cotaied i R. Timer A will cout up util reachig (hex). The, o the ext cout, the timer will be loaded with the value i the reset register where it will begi coutig up. Timer A will cotiue to begi with the reset value after each termial cout util a ew value is loaded ito the reset register. To retur to the ormal MIL-STD-175A operatio mode, the reset register must be loaded with zero. No other timer fuctios are chaged. The default value at power o ad after each hardware reset is zero. Load Timer B Reset Register LTBR E uctio: The Timer B Reset Register is loaded with the value cotaied i R. Timer B will cout up util reachig (hex). The, o the ext cout, the timer will be loaded with the value i the reset register where it will begi coutig up. Timer B will cotiue to begi with the reset value after each termial cout util a ew value is loaded ito the reset register. To retur to the ormal MIL-STD-175A operatio mode, the reset register must be loaded with zero. No other timer fuctios are chaged. The default value at power o ad after each hardware reset is zero. lags Affected: clocks WI additioal clocks Page 12 of 15
13 PACE 175AE BUILT-IN UNCTIONS Iput/Output Speed Improvemet Oe factor which limits the performace of 175A systems is the large overhead associated with the XIO istructio. Sice this istructio is defied as privileged by MIL-STD-175A, there are special steps which must be take by the microcode each time a XIO or VIO istructio is ecoutered. This causes the legth of the XIO istructio to be 2 to 3 clocks, depedig o whether a output or a iput is to be performed, eve though the actual I/O bus cycle is oly clocks. This ca restrict performace whe large blocks of data must be trasferred from memory to I/O devices, such as durig loads of the MMU page registers. The PACE175AE provides a ew istructio which allows a quick write of large blocks of data from memory to the I/ O space. The privileged istructio overhead must be performed oly oce i this istructio. Thus, the overhead pealty is paid up frot, ad the icremetal executio time is oly 8 clocks per data trasfer. I the case of the MMU page register load, if the complete set of istructio ad operad page registers is loaded usig XIO output istructios, a total of 512 XIO istructios must be executed at 2 clocks each. I additio to the XIOs, 512 Load Register from Memory istructios must be performed to place the data to be trasferred ito registers where it may be output by the XIO istructios. These istructios require 12 clocks each. Thus, the total executio time is 18,32 clocks. The same task performed by the IOMV BI would execute i,118 clocks a 78 percet improvemet. The IOMV istructio is described below. Block Move Memory to I/O IOMV uctio: See diagram, ext page. The memory block begiig at the address stored i R2 is moved to the I/O block begiig at the address stored i R. The umber of data words to be trasferred is stored i R1. The maximum trasfer size is 32,768, which is the umber of legal I/O output addresses. All memory data must reside withi the same address state if MMU is used. lags Affected: (22 + 8) clocks WI + 2(WD) Additioal clocks Page 13 of 15
14 PACE175AE BUILT-IN UNCTIONS CPU Registers R R1 R2 = I/O I/O1 I/O2 I/O3 I/O I/O Memory M1 M2 M3 M M Coclusio Though the PACE175AE provides a sigificat improvemet over the PACE175A o existig software, the fullest potetial of the processor may be obtaied oly by makig use of the BI istructios. Depedig o the tasks performed by the applicatio software, substatial improvemet i the system performace of the 175AE may be achieved through the use of the BIs. System performace i embedded cotrol applicatios was our goal whe desigig the PACE175AE, ad we believe that the BIs are just oe of the ehacemets which allowed us, ad you, to achieve that goal. Page 1 of 15
15 PACE 175AE BUILT-IN UNCTIONS REVISIONS DOCUMENT NUMBER: DOCUMENT TITLE: ANP16-3 APPLICATION NOTE - P175AE BUILT-IN UNCTIONS REV. ISSUE DATE ORIG. O CHANGE DESCRIPTION O CHANGE ORIG May-89 RKK New Data Sheet A Oct-5 JDB Added Pyramid logo Page 15 of 15
UNIVERSITY OF MORATUWA
UNIVERSITY OF MORATUWA FACULTY OF ENGINEERING DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING B.Sc. Egieerig 2014 Itake Semester 2 Examiatio CS2052 COMPUTER ARCHITECTURE Time allowed: 2 Hours Jauary 2016
More informationChapter 3 Classification of FFT Processor Algorithms
Chapter Classificatio of FFT Processor Algorithms The computatioal complexity of the Discrete Fourier trasform (DFT) is very high. It requires () 2 complex multiplicatios ad () complex additios [5]. As
More informationEnd Semester Examination CSE, III Yr. (I Sem), 30002: Computer Organization
Ed Semester Examiatio 2013-14 CSE, III Yr. (I Sem), 30002: Computer Orgaizatio Istructios: GROUP -A 1. Write the questio paper group (A, B, C, D), o frot page top of aswer book, as per what is metioed
More informationElementary Educational Computer
Chapter 5 Elemetary Educatioal Computer. Geeral structure of the Elemetary Educatioal Computer (EEC) The EEC coforms to the 5 uits structure defied by vo Neuma's model (.) All uits are preseted i a simplified
More informationCSC 220: Computer Organization Unit 11 Basic Computer Organization and Design
College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:
More informationChapter 3. Floating Point Arithmetic
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 3 Floatig Poit Arithmetic Review - Multiplicatio 0 1 1 0 = 6 multiplicad 32-bit ALU shift product right multiplier add
More informationComputer Systems - HS
What have we leared so far? Computer Systems High Level ENGG1203 2d Semester, 2017-18 Applicatios Sigals Systems & Cotrol Systems Computer & Embedded Systems Digital Logic Combiatioal Logic Sequetial Logic
More informationCOMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 4. The Processor. Part A Datapath Design
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter The Processor Part A path Desig Itroductio CPU performace factors Istructio cout Determied by ISA ad compiler. CPI ad
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationAppendix D. Controller Implementation
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Appedix D Cotroller Implemetatio Cotroller Implemetatios Combiatioal logic (sigle-cycle); Fiite state machie (multi-cycle, pipelied);
More informationEE 459/500 HDL Based Digital Design with Programmable Logic. Lecture 13 Control and Sequencing: Hardwired and Microprogrammed Control
EE 459/500 HDL Based Digital Desig with Programmable Logic Lecture 13 Cotrol ad Sequecig: Hardwired ad Microprogrammed Cotrol Refereces: Chapter s 4,5 from textbook Chapter 7 of M.M. Mao ad C.R. Kime,
More informationIMP: Superposer Integrated Morphometrics Package Superposition Tool
IMP: Superposer Itegrated Morphometrics Package Superpositio Tool Programmig by: David Lieber ( 03) Caisius College 200 Mai St. Buffalo, NY 4208 Cocept by: H. David Sheets, Dept. of Physics, Caisius College
More informationCMPT 125 Assignment 2 Solutions
CMPT 25 Assigmet 2 Solutios Questio (20 marks total) a) Let s cosider a iteger array of size 0. (0 marks, each part is 2 marks) it a[0]; I. How would you assig a poiter, called pa, to store the address
More informationChapter 4 The Datapath
The Ageda Chapter 4 The Datapath Based o slides McGraw-Hill Additioal material 24/25/26 Lewis/Marti Additioal material 28 Roth Additioal material 2 Taylor Additioal material 2 Farmer Tae the elemets that
More informationChapter 11. Friends, Overloaded Operators, and Arrays in Classes. Copyright 2014 Pearson Addison-Wesley. All rights reserved.
Chapter 11 Frieds, Overloaded Operators, ad Arrays i Classes Copyright 2014 Pearso Addiso-Wesley. All rights reserved. Overview 11.1 Fried Fuctios 11.2 Overloadig Operators 11.3 Arrays ad Classes 11.4
More informationData diverse software fault tolerance techniques
Data diverse software fault tolerace techiques Complemets desig diversity by compesatig for desig diversity s s limitatios Ivolves obtaiig a related set of poits i the program data space, executig the
More informationOne advantage that SONAR has over any other music-sequencing product I ve worked
*gajedra* D:/Thomso_Learig_Projects/Garrigus_163132/z_productio/z_3B2_3D_files/Garrigus_163132_ch17.3d, 14/11/08/16:26:39, 16:26, page: 647 17 CAL 101 Oe advatage that SONAR has over ay other music-sequecig
More informationChapter 2. C++ Basics. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 2 C++ Basics Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 2.1 Variables ad Assigmets 2.2 Iput ad Output 2.3 Data Types ad Expressios 2.4 Simple Flow of Cotrol 2.5 Program
More informationEE123 Digital Signal Processing
Last Time EE Digital Sigal Processig Lecture 7 Block Covolutio, Overlap ad Add, FFT Discrete Fourier Trasform Properties of the Liear covolutio through circular Today Liear covolutio with Overlap ad add
More informationChapter 1. Introduction to Computers and C++ Programming. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 1 Itroductio to Computers ad C++ Programmig Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 1.1 Computer Systems 1.2 Programmig ad Problem Solvig 1.3 Itroductio to C++ 1.4 Testig
More informationBezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only
Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of
More informationParabolic Path to a Best Best-Fit Line:
Studet Activity : Fidig the Least Squares Regressio Lie By Explorig the Relatioship betwee Slope ad Residuals Objective: How does oe determie a best best-fit lie for a set of data? Eyeballig it may be
More informationPerformance Plus Software Parameter Definitions
Performace Plus+ Software Parameter Defiitios/ Performace Plus Software Parameter Defiitios Chapma Techical Note-TG-5 paramete.doc ev-0-03 Performace Plus+ Software Parameter Defiitios/2 Backgroud ad Defiitios
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More information6.854J / J Advanced Algorithms Fall 2008
MIT OpeCourseWare http://ocw.mit.edu 6.854J / 18.415J Advaced Algorithms Fall 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 18.415/6.854 Advaced Algorithms
More informationChapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3
More informationDATA STRUCTURES. amortized analysis binomial heaps Fibonacci heaps union-find. Data structures. Appetizer. Appetizer
Data structures DATA STRUCTURES Static problems. Give a iput, produce a output. Ex. Sortig, FFT, edit distace, shortest paths, MST, max-flow,... amortized aalysis biomial heaps Fiboacci heaps uio-fid Dyamic
More informationChapter 4. Procedural Abstraction and Functions That Return a Value. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 4 Procedural Abstractio ad Fuctios That Retur a Value Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 4.1 Top-Dow Desig 4.2 Predefied Fuctios 4.3 Programmer-Defied Fuctios 4.4
More informationEE University of Minnesota. Midterm Exam #1. Prof. Matthew O'Keefe TA: Eric Seppanen. Department of Electrical and Computer Engineering
EE 4363 1 Uiversity of Miesota Midterm Exam #1 Prof. Matthew O'Keefe TA: Eric Seppae Departmet of Electrical ad Computer Egieerig Uiversity of Miesota Twi Cities Campus EE 4363 Itroductio to Microprocessors
More information1.2 Binomial Coefficients and Subsets
1.2. BINOMIAL COEFFICIENTS AND SUBSETS 13 1.2 Biomial Coefficiets ad Subsets 1.2-1 The loop below is part of a program to determie the umber of triagles formed by poits i the plae. for i =1 to for j =
More informationMath 10C Long Range Plans
Math 10C Log Rage Plas Uits: Evaluatio: Homework, projects ad assigmets 10% Uit Tests. 70% Fial Examiatio.. 20% Ay Uit Test may be rewritte for a higher mark. If the retest mark is higher, that mark will
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 1 Computers ad Programs 1 Objectives To uderstad the respective roles of hardware ad software i a computig system. To lear what computer scietists
More informationComputer Architecture. Microcomputer Architecture and Interfacing Colorado School of Mines Professor William Hoff
Computer rchitecture Microcomputer rchitecture ad Iterfacig Colorado School of Mies Professor William Hoff Computer Hardware Orgaizatio Processor Performs all computatios; coordiates data trasfer Iput
More informationMOTIF XF Extension Owner s Manual
MOTIF XF Extesio Ower s Maual Table of Cotets About MOTIF XF Extesio...2 What Extesio ca do...2 Auto settig of Audio Driver... 2 Auto settigs of Remote Device... 2 Project templates with Iput/ Output Bus
More informationIt just came to me that I 8.2 GRAPHS AND CONVERGENCE
44 Chapter 8 Discrete Mathematics: Fuctios o the Set of Natural Numbers (a) Take several odd, positive itegers for a ad write out eough terms of the 3N sequece to reach a repeatig loop (b) Show that ot
More informationBasic allocator mechanisms The course that gives CMU its Zip! Memory Management II: Dynamic Storage Allocation Mar 6, 2000.
5-23 The course that gives CM its Zip Memory Maagemet II: Dyamic Storage Allocatio Mar 6, 2000 Topics Segregated lists Buddy system Garbage collectio Mark ad Sweep Copyig eferece coutig Basic allocator
More informationStructuring Redundancy for Fault Tolerance. CSE 598D: Fault Tolerant Software
Structurig Redudacy for Fault Tolerace CSE 598D: Fault Tolerat Software What do we wat to achieve? Versios Damage Assessmet Versio 1 Error Detectio Iputs Versio 2 Voter Outputs State Restoratio Cotiued
More informationn Learn how resiliency strategies reduce risk n Discover automation strategies to reduce risk
Chapter Objectives Lear how resiliecy strategies reduce risk Discover automatio strategies to reduce risk Chapter #16: Architecture ad Desig Resiliecy ad Automatio Strategies 2 Automatio/Scriptig Resiliet
More informationLecture 1: Introduction and Strassen s Algorithm
5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access
More informationImproving Template Based Spike Detection
Improvig Template Based Spike Detectio Kirk Smith, Member - IEEE Portlad State Uiversity petra@ee.pdx.edu Abstract Template matchig algorithms like SSE, Covolutio ad Maximum Likelihood are well kow for
More informationAlpha Individual Solutions MAΘ National Convention 2013
Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5
More informationChapter 10. Defining Classes. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 10 Defiig Classes Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 10.1 Structures 10.2 Classes 10.3 Abstract Data Types 10.4 Itroductio to Iheritace Copyright 2015 Pearso Educatio,
More informationSorting in Linear Time. Data Structures and Algorithms Andrei Bulatov
Sortig i Liear Time Data Structures ad Algorithms Adrei Bulatov Algorithms Sortig i Liear Time 7-2 Compariso Sorts The oly test that all the algorithms we have cosidered so far is compariso The oly iformatio
More informationEE260: Digital Design, Spring /16/18. n Example: m 0 (=x 1 x 2 ) is adjacent to m 1 (=x 1 x 2 ) and m 2 (=x 1 x 2 ) but NOT m 3 (=x 1 x 2 )
EE26: Digital Desig, Sprig 28 3/6/8 EE 26: Itroductio to Digital Desig Combiatioal Datapath Yao Zheg Departmet of Electrical Egieerig Uiversity of Hawaiʻi at Māoa Combiatioal Logic Blocks Multiplexer Ecoders/Decoders
More informationThe Magma Database file formats
The Magma Database file formats Adrew Gaylard, Bret Pikey, ad Mart-Mari Breedt Johaesburg, South Africa 15th May 2006 1 Summary Magma is a ope-source object database created by Chris Muller, of Kasas City,
More informationPolynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0
Polyomial Fuctios ad Models 1 Learig Objectives 1. Idetify polyomial fuctios ad their degree 2. Graph polyomial fuctios usig trasformatios 3. Idetify the real zeros of a polyomial fuctio ad their multiplicity
More informationComputer Architecture
Computer Architecture Overview Prof. Tie-Fu Che Dept. of Computer Sciece Natioal Chug Cheg Uiv Sprig 2002 Overview- Computer Architecture Course Focus Uderstadig the desig techiques, machie structures,
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 6 Defiig Fuctios Pytho Programmig, 2/e 1 Objectives To uderstad why programmers divide programs up ito sets of cooperatig fuctios. To be able to
More informationImprovement of the Orthogonal Code Convolution Capabilities Using FPGA Implementation
Improvemet of the Orthogoal Code Covolutio Capabilities Usig FPGA Implemetatio Naima Kaabouch, Member, IEEE, Apara Dhirde, Member, IEEE, Saleh Faruque, Member, IEEE Departmet of Electrical Egieerig, Uiversity
More informationThe number n of subintervals times the length h of subintervals gives length of interval (b-a).
Simulator with MadMath Kit: Riema Sums (Teacher s pages) I your kit: 1. GeoGebra file: Ready-to-use projector sized simulator: RiemaSumMM.ggb 2. RiemaSumMM.pdf (this file) ad RiemaSumMMEd.pdf (educator's
More informationCHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs
CHAPTER IV: GRAPH THEORY Sectio : Itroductio to Graphs Sice this class is called Number-Theoretic ad Discrete Structures, it would be a crime to oly focus o umber theory regardless how woderful those topics
More informationDescriptive Statistics Summary Lists
Chapter 209 Descriptive Statistics Summary Lists Itroductio This procedure is used to summarize cotiuous data. Large volumes of such data may be easily summarized i statistical lists of meas, couts, stadard
More informationFast Fourier Transform (FFT) Algorithms
Fast Fourier Trasform FFT Algorithms Relatio to the z-trasform elsewhere, ozero, z x z X x [ ] 2 ~ elsewhere,, ~ e j x X x x π j e z z X X π 2 ~ The DFS X represets evely spaced samples of the z- trasform
More informationCIS 121 Data Structures and Algorithms with Java Spring Stacks, Queues, and Heaps Monday, February 18 / Tuesday, February 19
CIS Data Structures ad Algorithms with Java Sprig 09 Stacks, Queues, ad Heaps Moday, February 8 / Tuesday, February 9 Stacks ad Queues Recall the stack ad queue ADTs (abstract data types from lecture.
More informationSouth Slave Divisional Education Council. Math 10C
South Slave Divisioal Educatio Coucil Math 10C Curriculum Package February 2012 12 Strad: Measuremet Geeral Outcome: Develop spatial sese ad proportioal reasoig It is expected that studets will: 1. Solve
More informationSpectral leakage and windowing
EEL33: Discrete-Time Sigals ad Systems Spectral leakage ad widowig. Itroductio Spectral leakage ad widowig I these otes, we itroduce the idea of widowig for reducig the effects of spectral leakage, ad
More informationAnalysis Metrics. Intro to Algorithm Analysis. Slides. 12. Alg Analysis. 12. Alg Analysis
Itro to Algorithm Aalysis Aalysis Metrics Slides. Table of Cotets. Aalysis Metrics 3. Exact Aalysis Rules 4. Simple Summatio 5. Summatio Formulas 6. Order of Magitude 7. Big-O otatio 8. Big-O Theorems
More informationCMSC Computer Architecture Lecture 12: Virtual Memory. Prof. Yanjing Li University of Chicago
CMSC 22200 Computer Architecture Lecture 12: Virtual Memory Prof. Yajig Li Uiversity of Chicago A System with Physical Memory Oly Examples: most Cray machies early PCs Memory early all embedded systems
More informationLecture 2. RTL Design Methodology. Transition from Pseudocode & Interface to a Corresponding Block Diagram
Lecture 2 RTL Desig Methodology Trasitio from Pseudocode & Iterface to a Correspodig Block Diagram Structure of a Typical Digital Data Iputs Datapath (Executio Uit) Data Outputs System Cotrol Sigals Status
More informationThe isoperimetric problem on the hypercube
The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose
More informationMath Section 2.2 Polynomial Functions
Math 1330 - Sectio. Polyomial Fuctios Our objectives i workig with polyomial fuctios will be, first, to gather iformatio about the graph of the fuctio ad, secod, to use that iformatio to geerate a reasoably
More informationEVALUATION OF TRIGONOMETRIC FUNCTIONS
EVALUATION OF TRIGONOMETRIC FUNCTIONS Whe first exposed to trigoometric fuctios i high school studets are expected to memorize the values of the trigoometric fuctios of sie cosie taget for the special
More informationAutomatic Generation of Polynomial-Basis Multipliers in GF (2 n ) using Recursive VHDL
Automatic Geeratio of Polyomial-Basis Multipliers i GF (2 ) usig Recursive VHDL J. Nelso, G. Lai, A. Teca Abstract Multiplicatio i GF (2 ) is very commoly used i the fields of cryptography ad error correctig
More informationK-NET bus. When several turrets are connected to the K-Bus, the structure of the system is as showns
K-NET bus The K-Net bus is based o the SPI bus but it allows to addressig may differet turrets like the I 2 C bus. The K-Net is 6 a wires bus (4 for SPI wires ad 2 additioal wires for request ad ackowledge
More informationPseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance
Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Pseudocode ( 1.1) High-level descriptio of a algorithm More structured
More information9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence
_9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to
More informationCreating Exact Bezier Representations of CST Shapes. David D. Marshall. California Polytechnic State University, San Luis Obispo, CA , USA
Creatig Exact Bezier Represetatios of CST Shapes David D. Marshall Califoria Polytechic State Uiversity, Sa Luis Obispo, CA 93407-035, USA The paper presets a method of expressig CST shapes pioeered by
More informationELEG 5173L Digital Signal Processing Introduction to TMS320C6713 DSK
Departmet of Electrical Egieerig Uiversity of Arasas ELEG 5173L Digital Sigal Processig Itroductio to TMS320C6713 DSK Dr. Jigia Wu wuj@uar.edu ANALOG V.S DIGITAL 2 Aalog sigal processig ASP Aalog sigal
More informationCOMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 4. The Processor. Single-Cycle Disadvantages & Advantages
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 4 The Processor Pipeliig Sigle-Cycle Disadvatages & Advatages Clk Uses the clock cycle iefficietly the clock cycle must
More informationWeston Anniversary Fund
Westo Olie Applicatio Guide 2018 1 This guide is desiged to help charities applyig to the Westo to use our olie applicatio form. The Westo is ope to applicatios from 5th Jauary 2018 ad closes o 30th Jue
More informationn n B. How many subsets of C are there of cardinality n. We are selecting elements for such a
4. [10] Usig a combiatorial argumet, prove that for 1: = 0 = Let A ad B be disjoit sets of cardiality each ad C = A B. How may subsets of C are there of cardiality. We are selectig elemets for such a subset
More informationLecture 28: Data Link Layer
Automatic Repeat Request (ARQ) 2. Go ack N ARQ Although the Stop ad Wait ARQ is very simple, you ca easily show that it has very the low efficiecy. The low efficiecy comes from the fact that the trasmittig
More informationLoad balanced Parallel Prime Number Generator with Sieve of Eratosthenes on Cluster Computers *
Load balaced Parallel Prime umber Geerator with Sieve of Eratosthees o luster omputers * Soowook Hwag*, Kyusik hug**, ad Dogseug Kim* *Departmet of Electrical Egieerig Korea Uiversity Seoul, -, Rep. of
More informationFilter design. 1 Design considerations: a framework. 2 Finite impulse response (FIR) filter design
Filter desig Desig cosideratios: a framework C ı p ı p H(f) Aalysis of fiite wordlegth effects: I practice oe should check that the quatisatio used i the implemetatio does ot degrade the performace of
More informationDigital System Design
July, 22 9:55 vra235_ch Sheet umber Page umber 65 black chapter Digital System Desig a b c d e f g h 8 7 6 5 4 3 2. Bd3 g6+, Ke8 d8 65 July, 22 9:55 vra235_ch Sheet umber 2 Page umber 66 black 66 CHAPTER
More informationtop() Applications of Stacks
CS22 Algorithms ad Data Structures MW :00 am - 2: pm, MSEC 0 Istructor: Xiao Qi Lecture 6: Stacks ad Queues Aoucemets Quiz results Homework 2 is available Due o September 29 th, 2004 www.cs.mt.edu~xqicoursescs22
More informationHow do we evaluate algorithms?
F2 Readig referece: chapter 2 + slides Algorithm complexity Big O ad big Ω To calculate ruig time Aalysis of recursive Algorithms Next time: Litterature: slides mostly The first Algorithm desig methods:
More informationThe following algorithms have been tested as a method of converting an I.F. from 16 to 512 MHz to 31 real 16 MHz USB channels:
DBE Memo#1 MARK 5 MEMO #18 MASSACHUSETTS INSTITUTE OF TECHNOLOGY HAYSTACK OBSERVATORY WESTFORD, MASSACHUSETTS 1886 November 19, 24 Telephoe: 978-692-4764 Fax: 781-981-59 To: From: Mark 5 Developmet Group
More informationSolution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring, Instructions:
CS 604 Data Structures Midterm Sprig, 00 VIRG INIA POLYTECHNIC INSTITUTE AND STATE U T PROSI M UNI VERSI TY Istructios: Prit your ame i the space provided below. This examiatio is closed book ad closed
More information1. SWITCHING FUNDAMENTALS
. SWITCING FUNDMENTLS Switchig is the provisio of a o-demad coectio betwee two ed poits. Two distict switchig techiques are employed i commuicatio etwors-- circuit switchig ad pacet switchig. Circuit switchig
More informationAlgorithms for Disk Covering Problems with the Most Points
Algorithms for Disk Coverig Problems with the Most Poits Bi Xiao Departmet of Computig Hog Kog Polytechic Uiversity Hug Hom, Kowloo, Hog Kog csbxiao@comp.polyu.edu.hk Qigfeg Zhuge, Yi He, Zili Shao, Edwi
More informationOnes Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationLecture 3. RTL Design Methodology. Transition from Pseudocode & Interface to a Corresponding Block Diagram
Lecture 3 RTL Desig Methodology Trasitio from Pseudocode & Iterface to a Correspodig Block Diagram Structure of a Typical Digital Data Iputs Datapath (Executio Uit) Data Outputs System Cotrol Sigals Status
More informationGuide to Applying Online
Guide to Applyig Olie Itroductio Respodig to requests for additioal iformatio Reportig: submittig your moitorig or ed of grat Pledges: submittig your Itroductio This guide is to help charities submit their
More informationThe Nature of Light. Chapter 22. Geometric Optics Using a Ray Approximation. Ray Approximation
The Nature of Light Chapter Reflectio ad Refractio of Light Sectios: 5, 8 Problems: 6, 7, 4, 30, 34, 38 Particles of light are called photos Each photo has a particular eergy E = h ƒ h is Plack s costat
More informationCIS 121 Data Structures and Algorithms with Java Spring Stacks and Queues Monday, February 12 / Tuesday, February 13
CIS Data Structures ad Algorithms with Java Sprig 08 Stacks ad Queues Moday, February / Tuesday, February Learig Goals Durig this lab, you will: Review stacks ad queues. Lear amortized ruig time aalysis
More informationCS Polygon Scan Conversion. Slide 1
CS 112 - Polygo Sca Coversio Slide 1 Polygo Classificatio Covex All iterior agles are less tha 180 degrees Cocave Iterior agles ca be greater tha 180 degrees Degeerate polygos If all vertices are colliear
More informationA New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method
A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro
More informationBACHMANN-LANDAU NOTATIONS. Lecturer: Dr. Jomar F. Rabajante IMSP, UPLB MATH 174: Numerical Analysis I 1 st Sem AY
BACHMANN-LANDAU NOTATIONS Lecturer: Dr. Jomar F. Rabajate IMSP, UPLB MATH 174: Numerical Aalysis I 1 st Sem AY 018-019 RANKING OF FUNCTIONS Name Big-Oh Eamples Costat O(1 10 Logarithmic O(log log, log(
More informationAvid Interplay Bundle
Avid Iterplay Budle Versio 2.5 Cofigurator ReadMe Overview This documet provides a overview of Iterplay Budle v2.5 ad describes how to ru the Iterplay Budle cofiguratio tool. Iterplay Budle v2.5 refers
More informationGetting Started. Getting Started - 1
Gettig Started Gettig Started - 1 Issue 1 Overview of Gettig Started Overview of Gettig Started This sectio explais the basic operatios of the AUDIX system. It describes how to: Log i ad log out of the
More informationChapter 5. Functions for All Subtasks. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 5 Fuctios for All Subtasks Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 5.1 void Fuctios 5.2 Call-By-Referece Parameters 5.3 Usig Procedural Abstractio 5.4 Testig ad Debuggig
More informationComputer Graphics Hardware An Overview
Computer Graphics Hardware A Overview Graphics System Moitor Iput devices CPU/Memory GPU Raster Graphics System Raster: A array of picture elemets Based o raster-sca TV techology The scree (ad a picture)
More informationLecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions
U.C. Berkeley CS170 : Algorithms Midterm 1 Solutios Lecturers: Sajam Garg ad Prasad Raghavedra Feb 1, 017 Midterm 1 Solutios 1. (4 poits) For the directed graph below, fid all the strogly coected compoets
More informationCSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)
CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a
More information1 Enterprise Modeler
1 Eterprise Modeler Itroductio I BaaERP, a Busiess Cotrol Model ad a Eterprise Structure Model for multi-site cofiguratios are itroduced. Eterprise Structure Model Busiess Cotrol Models Busiess Fuctio
More informationComputers and Scientific Thinking
Computers ad Scietific Thikig David Reed, Creighto Uiversity Chapter 15 JavaScript Strigs 1 Strigs as Objects so far, your iteractive Web pages have maipulated strigs i simple ways use text box to iput
More informationMajor CSL Write your name and entry no on every sheet of the answer script. Time 2 Hrs Max Marks 70
NOTE:. Attempt all seve questios. Major CSL 02 2. Write your ame ad etry o o every sheet of the aswer script. Time 2 Hrs Max Marks 70 Q No Q Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Total MM 6 2 4 0 8 4 6 70 Q. Write a
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 22 Database Recovery Techiques Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio Recovery algorithms Recovery cocepts Write-ahead
More informationGeneration of Distributed Arithmetic Designs for Reconfigurable Applications
Geeratio of Distributed Arithmetic Desigs for Recofigurable Applicatios Christophe Bobda, Ali Ahmadiia, Jürge Teich Uiversity of Erlage-Nuremberg Departmet of computer sciece Am Weichselgarte 3, 91058
More information