SlideShare a Scribd company logo
1 of 20
Discrete Transforms & Number Theoretical
[06-88-529-1-2016W]
A
Project Presentation
On
An efficient binary multiplier design for high speed
applications using Karatsuba algorithm and Urdhva-
Tiryagbhyam algorithm
Instructor : Dr. Huapeng Wu
Presented by : Rajan Savaliya (Student ID# 104519325)
Savankumar Darji (Student ID# 104519347)
Abstract
Aim of this research paper is to reduce number of binary multiplication
that can save time as well as hardware requirement for implementation
of binary multiplier using algorithms like Karatsuba and Urdhva-
Tiryagbhyam. To implement binary multiplier, the complexity of design
depends on number of multiplication for calculating the product. So, in
this paper the main target of author is to reduce number of
multiplication with the help of ancient Vedic and classical mathematics.
Conventional method of multiplication and its
complexity
Karatsuba Multiplication
This algorithm reduces the number of multiplication comparing to
conventional method of multiplication.
For example:
A 2-digit decimal number can be represented in below convention,
a = 10p+q , b = 10r+s
Let’s say 87 can be represented as 87 = 10(8)+7 and 56 = 10(5)+6
a = 10(p)+q b = 10(r)+s
doing the math by a x b = (10p+q) x (10r+s) we will get
a x b = (p x r)100 + ((p x s) + (r x q))10 + (q x s)
a x b = (p x r)100 + ((p x s) + (r x q))10 + (q x s)
# of multiplication: 1 2 3 4
But if we replace multiplication by several and subtraction we will get
this equation:
a x b = u x 100 + v x 10 + w
Here, u = p x r
w = q x s
v = (p + q) x (r + s) – u - w
These multiplications are called auxiliary multiplications. Here, notice
that u, w and v have only 3 multiplication !
3 Multiplication by
Karatsuba
Block diagram of Karatsuba multiplication
8 digit binary multiplication using Karatsuba
Algorithm
Multiplication Comparison
Complexity of Karatsuba multiplication
Total delay required to compute n digit
multiplication
Urdhva-Tiryagbhyam Multiplication
It is the one of the 16 formula which is given in Appendix of Atharvaveda, one
of the six Veda from Indian Hinduism. It can compute the N digit multiplication
with very fewer and quicker steps when the number of digits are lower i.e. less
than 5. The reason behind that is the number of steps for computing
multiplication is proportional to the number of digit.
For Example: 2 binary digit Multiplication
11 × 11: P0 = 1 × 1 = 1
P1 = (1 × 1) + (1 × 1) + carry_0 = 0 (carry_1 = 1)
P2 = (1 × 1) + carry_0 = 0 (carry_1 = 1)
Answer = 1001
Line representation of the Method:
11 × 11
Calculation for P2 Calculation for P1 Calculation for P1
1 1 1 1 1 1
+ carry_0
1 1 1 1 1 1
(1 × 1) + 1 (carry_0) = (1 × 1) + (1 × 1) = (1 × 1) =
1 0 1 0 1
carry_1 Answer = 1 0 0 1
Line representation of 4 digit multiplication
using Urdhva-Tiryagbhyam Algorithm:
• P0 = a0b0 (1 digit)
• P1 = LSB{ a1bo+a0b1 } (2 digit)
• P2 = LSB{ a2bo+a1b1+a0b2+MSB(P1) }
(3
digit)
• P3=LSB{ a3bo+a2b1+a1b2+a0b3
+MSB(P2) } (3 digit)
• P4=LSB{ a3b1+a2b2+a1b3+MSB(P3) }
(3 digit)
• P5=LSB{a3b2+a2b3+MSB(P4)}(3 digit)
• P6=LSB{a3b3+MSB(P5)} (2 digit)
• P7=MSB(P6) (1 digit)
Combinational logic circuit of 4 digit binary
Urdhva-Tiryagbhyam multiplier :
Advantages of the multiplier :
Parameters Urdhva-
Tiryagbhyam
Multiplier
Proposed
Multiplier
Length 8 bits 8 bits
Delay 28.27 ns 9.396 ns
References
1) “Vedic mathematics”, Swami Sri Bharati Krsna Thirthaji Maharaja,
Motilal Banarasidass Indological publishers and Book sellers,
1965.
2) Poornima M, Shivaraj Kumar Patil, Shivukumar , Shridhar K P ,
Sanjay H, “Implementation of Multiplier using Vedic Algorithm”,
International Journal of Innovative Technology and Exploring
Engineering (IJITEE), ISSN: 2278-3075, Volume-2, Issue-6, pp.
219-223, May 2013.
3) http://www.stoimen.com/blog/2012/05/15/computer-algorithms-
karatsuba-fast-multiplication/
4) http://www.math.uwaterloo.ca/~anayak/courses/ece103-
s10/notes/recursion.pdf
5) http://courses.csail.mit.edu/6.006/spring11/exams/notes3-
karatsuba
6) https://class.coursera.org/algo-004/lecture
7) http://courses.csail.mit.edu/6.006/spring11/exams/notes3-
karatsuba

More Related Content

What's hot

Formal methods 4 - Z notation
Formal methods   4 - Z notationFormal methods   4 - Z notation
Formal methods 4 - Z notationVlad Patryshev
 
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurQuiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurVivekananda Samiti
 
Calculus II - 26
Calculus II - 26Calculus II - 26
Calculus II - 26David Mao
 
Double Q-learning Paper Reading
Double Q-learning Paper ReadingDouble Q-learning Paper Reading
Double Q-learning Paper ReadingTakato Yamazaki
 
Sequence and Series in Discrete Structure
Sequence and Series in Discrete Structure Sequence and Series in Discrete Structure
Sequence and Series in Discrete Structure Zain Abid
 
Sequence and Series Word File || Discrete Structure
Sequence and Series Word File || Discrete StructureSequence and Series Word File || Discrete Structure
Sequence and Series Word File || Discrete StructureZain Abid
 
Lecture 3 - Introduction to Interpolation
Lecture 3 - Introduction to InterpolationLecture 3 - Introduction to Interpolation
Lecture 3 - Introduction to InterpolationEric Cochran
 
Datamining 3rd Naivebayes
Datamining 3rd NaivebayesDatamining 3rd Naivebayes
Datamining 3rd Naivebayessesejun
 
PAC Bayesian for Deep Learning
PAC Bayesian for Deep LearningPAC Bayesian for Deep Learning
PAC Bayesian for Deep LearningMark Chang
 
November 17, 2015
November 17, 2015November 17, 2015
November 17, 2015khyps13
 
Introduction to modern Variational Inference.
Introduction to modern Variational Inference.Introduction to modern Variational Inference.
Introduction to modern Variational Inference.Tomasz Kusmierczyk
 
Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Eliezer Silva
 
Numerical on dichotomous search
Numerical on dichotomous searchNumerical on dichotomous search
Numerical on dichotomous searchSumita Das
 
Final exam review
Final exam review Final exam review
Final exam review Tyler Murphy
 
Real life Application of maximum and minimum
Real life Application of maximum and minimumReal life Application of maximum and minimum
Real life Application of maximum and minimumNiloy Biswas
 
Parallel Bayesian Optimization
Parallel Bayesian OptimizationParallel Bayesian Optimization
Parallel Bayesian OptimizationSri Ambati
 

What's hot (20)

Formal methods 4 - Z notation
Formal methods   4 - Z notationFormal methods   4 - Z notation
Formal methods 4 - Z notation
 
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurQuiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Quiz3 | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
 
Calculus II - 26
Calculus II - 26Calculus II - 26
Calculus II - 26
 
Double Q-learning Paper Reading
Double Q-learning Paper ReadingDouble Q-learning Paper Reading
Double Q-learning Paper Reading
 
Lecture 4 f17
Lecture 4 f17Lecture 4 f17
Lecture 4 f17
 
Lecture 11 f17
Lecture 11 f17Lecture 11 f17
Lecture 11 f17
 
Sequence and Series in Discrete Structure
Sequence and Series in Discrete Structure Sequence and Series in Discrete Structure
Sequence and Series in Discrete Structure
 
Sequence and Series Word File || Discrete Structure
Sequence and Series Word File || Discrete StructureSequence and Series Word File || Discrete Structure
Sequence and Series Word File || Discrete Structure
 
Lecture 3 - Introduction to Interpolation
Lecture 3 - Introduction to InterpolationLecture 3 - Introduction to Interpolation
Lecture 3 - Introduction to Interpolation
 
Datamining 3rd Naivebayes
Datamining 3rd NaivebayesDatamining 3rd Naivebayes
Datamining 3rd Naivebayes
 
PAC Bayesian for Deep Learning
PAC Bayesian for Deep LearningPAC Bayesian for Deep Learning
PAC Bayesian for Deep Learning
 
Analysis of algo
Analysis of algoAnalysis of algo
Analysis of algo
 
November 17, 2015
November 17, 2015November 17, 2015
November 17, 2015
 
Introduction to modern Variational Inference.
Introduction to modern Variational Inference.Introduction to modern Variational Inference.
Introduction to modern Variational Inference.
 
talk MCMC & SMC 2004
talk MCMC & SMC 2004talk MCMC & SMC 2004
talk MCMC & SMC 2004
 
Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space
 
Numerical on dichotomous search
Numerical on dichotomous searchNumerical on dichotomous search
Numerical on dichotomous search
 
Final exam review
Final exam review Final exam review
Final exam review
 
Real life Application of maximum and minimum
Real life Application of maximum and minimumReal life Application of maximum and minimum
Real life Application of maximum and minimum
 
Parallel Bayesian Optimization
Parallel Bayesian OptimizationParallel Bayesian Optimization
Parallel Bayesian Optimization
 

Viewers also liked

RSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis
RSA Key Extraction via Low-Bandwidth Acoustic CryptanalysisRSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis
RSA Key Extraction via Low-Bandwidth Acoustic CryptanalysisDusan Klinec
 
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...IAEME Publication
 
Ambientes de aprendizaje
Ambientes de aprendizajeAmbientes de aprendizaje
Ambientes de aprendizajegaabyescobedo
 
Product concept - TripNaut
Product concept - TripNautProduct concept - TripNaut
Product concept - TripNautCaio Donini
 
Guia crustáceos y mirápodos
Guia crustáceos y mirápodosGuia crustáceos y mirápodos
Guia crustáceos y mirápodosgabytta
 
5 Ways to Streamline Your Onboarding Process
5 Ways to Streamline Your Onboarding Process5 Ways to Streamline Your Onboarding Process
5 Ways to Streamline Your Onboarding ProcessPyramid Solutions, Inc.
 
minimum spanning trees Algorithm
minimum spanning trees Algorithm minimum spanning trees Algorithm
minimum spanning trees Algorithm sachin varun
 
New york police museum
New york police museumNew york police museum
New york police museumMarta Martín
 
The museum of bad art
The museum of bad artThe museum of bad art
The museum of bad artMarta Martín
 
Ingles (natural reserve and home remedies)
Ingles (natural reserve and home remedies)Ingles (natural reserve and home remedies)
Ingles (natural reserve and home remedies)Marta Martín
 
Dicaprius felchius(basque,wild pig) protection
Dicaprius felchius(basque,wild pig) protectionDicaprius felchius(basque,wild pig) protection
Dicaprius felchius(basque,wild pig) protectionMarta Martín
 
A presentation on prim's and kruskal's algorithm
A presentation on prim's and kruskal's algorithmA presentation on prim's and kruskal's algorithm
A presentation on prim's and kruskal's algorithmGaurav Kolekar
 
Minimum spanning tree algorithms by ibrahim_alfayoumi
Minimum spanning tree algorithms by ibrahim_alfayoumiMinimum spanning tree algorithms by ibrahim_alfayoumi
Minimum spanning tree algorithms by ibrahim_alfayoumiIbrahim Alfayoumi
 
KRUSKAL'S algorithm from chaitra
KRUSKAL'S algorithm from chaitraKRUSKAL'S algorithm from chaitra
KRUSKAL'S algorithm from chaitraguest1f4fb3
 

Viewers also liked (20)

RSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis
RSA Key Extraction via Low-Bandwidth Acoustic CryptanalysisRSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis
RSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis
 
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...
A COMPARATIVE STUDY OF BS8110 AND EUROCODE 2 STANDARDS FOR DESIGN OF A CONTIN...
 
Ambientes de aprendizaje
Ambientes de aprendizajeAmbientes de aprendizaje
Ambientes de aprendizaje
 
PI_DougJost_010916
PI_DougJost_010916PI_DougJost_010916
PI_DougJost_010916
 
Product concept - TripNaut
Product concept - TripNautProduct concept - TripNaut
Product concept - TripNaut
 
Focus-Profile
Focus-ProfileFocus-Profile
Focus-Profile
 
Guia crustáceos y mirápodos
Guia crustáceos y mirápodosGuia crustáceos y mirápodos
Guia crustáceos y mirápodos
 
5 Ways to Streamline Your Onboarding Process
5 Ways to Streamline Your Onboarding Process5 Ways to Streamline Your Onboarding Process
5 Ways to Streamline Your Onboarding Process
 
minimum spanning trees Algorithm
minimum spanning trees Algorithm minimum spanning trees Algorithm
minimum spanning trees Algorithm
 
Unusual museum ane
Unusual museum aneUnusual museum ane
Unusual museum ane
 
New york police museum
New york police museumNew york police museum
New york police museum
 
The museum of bad art
The museum of bad artThe museum of bad art
The museum of bad art
 
Ingles (natural reserve and home remedies)
Ingles (natural reserve and home remedies)Ingles (natural reserve and home remedies)
Ingles (natural reserve and home remedies)
 
Dicaprius felchius(basque,wild pig) protection
Dicaprius felchius(basque,wild pig) protectionDicaprius felchius(basque,wild pig) protection
Dicaprius felchius(basque,wild pig) protection
 
A presentation on prim's and kruskal's algorithm
A presentation on prim's and kruskal's algorithmA presentation on prim's and kruskal's algorithm
A presentation on prim's and kruskal's algorithm
 
Kruskal’s Algorithm
Kruskal’s AlgorithmKruskal’s Algorithm
Kruskal’s Algorithm
 
Minimum spanning tree algorithms by ibrahim_alfayoumi
Minimum spanning tree algorithms by ibrahim_alfayoumiMinimum spanning tree algorithms by ibrahim_alfayoumi
Minimum spanning tree algorithms by ibrahim_alfayoumi
 
KRUSKAL'S algorithm from chaitra
KRUSKAL'S algorithm from chaitraKRUSKAL'S algorithm from chaitra
KRUSKAL'S algorithm from chaitra
 
Museu d'història de catalunya
Museu d'història de catalunyaMuseu d'història de catalunya
Museu d'història de catalunya
 
Kruskal Algorithm
Kruskal AlgorithmKruskal Algorithm
Kruskal Algorithm
 

Similar to Project PPT slides_student_id#104519347

Matlab polynimials and curve fitting
Matlab polynimials and curve fittingMatlab polynimials and curve fitting
Matlab polynimials and curve fittingAmeen San
 
Polynomials and Curve Fitting in MATLAB
Polynomials and Curve Fitting in MATLABPolynomials and Curve Fitting in MATLAB
Polynomials and Curve Fitting in MATLABShameer Ahmed Koya
 
Advanced matlab codigos matematicos
Advanced matlab codigos matematicosAdvanced matlab codigos matematicos
Advanced matlab codigos matematicosKmilo Bolaños
 
Appendex b
Appendex bAppendex b
Appendex bswavicky
 
Binu Siva Singh Final.pptx
Binu Siva Singh Final.pptxBinu Siva Singh Final.pptx
Binu Siva Singh Final.pptxdivisatish
 
Kolev skalna2018 article-exact_solutiontoa_parametricline
Kolev skalna2018 article-exact_solutiontoa_parametriclineKolev skalna2018 article-exact_solutiontoa_parametricline
Kolev skalna2018 article-exact_solutiontoa_parametriclineAlina Barbulescu
 
Applied Algorithms and Structures week999
Applied Algorithms and Structures week999Applied Algorithms and Structures week999
Applied Algorithms and Structures week999fashiontrendzz20
 
Karatsuba algorithm for fast mltiplication
Karatsuba algorithm for fast mltiplicationKaratsuba algorithm for fast mltiplication
Karatsuba algorithm for fast mltiplicationAtul Singh
 
The binomial theorem
The binomial theoremThe binomial theorem
The binomial theoremparassini
 
32 approximation, differentiation and integration of power series x
32 approximation, differentiation and integration of power series x32 approximation, differentiation and integration of power series x
32 approximation, differentiation and integration of power series xmath266
 
Multinomial Logistic Regression with Apache Spark
Multinomial Logistic Regression with Apache SparkMultinomial Logistic Regression with Apache Spark
Multinomial Logistic Regression with Apache SparkDB Tsai
 
Alpine Spark Implementation - Technical
Alpine Spark Implementation - TechnicalAlpine Spark Implementation - Technical
Alpine Spark Implementation - Technicalalpinedatalabs
 
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurMid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurVivekananda Samiti
 
A New Deterministic RSA-Factoring Algorithm
A New Deterministic RSA-Factoring AlgorithmA New Deterministic RSA-Factoring Algorithm
A New Deterministic RSA-Factoring AlgorithmJim Jimenez
 
Demystification of vedic multiplication algorithm
Demystification of vedic multiplication algorithmDemystification of vedic multiplication algorithm
Demystification of vedic multiplication algorithmRITES Ltd
 

Similar to Project PPT slides_student_id#104519347 (20)

Matlab polynimials and curve fitting
Matlab polynimials and curve fittingMatlab polynimials and curve fitting
Matlab polynimials and curve fitting
 
Polynomials and Curve Fitting in MATLAB
Polynomials and Curve Fitting in MATLABPolynomials and Curve Fitting in MATLAB
Polynomials and Curve Fitting in MATLAB
 
Advanced matlab codigos matematicos
Advanced matlab codigos matematicosAdvanced matlab codigos matematicos
Advanced matlab codigos matematicos
 
Appendex b
Appendex bAppendex b
Appendex b
 
Binu Siva Singh Final.pptx
Binu Siva Singh Final.pptxBinu Siva Singh Final.pptx
Binu Siva Singh Final.pptx
 
Kolev skalna2018 article-exact_solutiontoa_parametricline
Kolev skalna2018 article-exact_solutiontoa_parametriclineKolev skalna2018 article-exact_solutiontoa_parametricline
Kolev skalna2018 article-exact_solutiontoa_parametricline
 
Applied Algorithms and Structures week999
Applied Algorithms and Structures week999Applied Algorithms and Structures week999
Applied Algorithms and Structures week999
 
Lecture50
Lecture50Lecture50
Lecture50
 
Karatsuba algorithm for fast mltiplication
Karatsuba algorithm for fast mltiplicationKaratsuba algorithm for fast mltiplication
Karatsuba algorithm for fast mltiplication
 
The binomial theorem
The binomial theoremThe binomial theorem
The binomial theorem
 
32 approximation, differentiation and integration of power series x
32 approximation, differentiation and integration of power series x32 approximation, differentiation and integration of power series x
32 approximation, differentiation and integration of power series x
 
Multinomial Logistic Regression with Apache Spark
Multinomial Logistic Regression with Apache SparkMultinomial Logistic Regression with Apache Spark
Multinomial Logistic Regression with Apache Spark
 
Alpine Spark Implementation - Technical
Alpine Spark Implementation - TechnicalAlpine Spark Implementation - Technical
Alpine Spark Implementation - Technical
 
algorithm Unit 2
algorithm Unit 2 algorithm Unit 2
algorithm Unit 2
 
Unit 2 in daa
Unit 2 in daaUnit 2 in daa
Unit 2 in daa
 
Divide and conquer
Divide and conquerDivide and conquer
Divide and conquer
 
LSH
LSHLSH
LSH
 
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT KanpurMid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
Mid semexam | Theory of Computation | Akash Anand | MTH 401A | IIT Kanpur
 
A New Deterministic RSA-Factoring Algorithm
A New Deterministic RSA-Factoring AlgorithmA New Deterministic RSA-Factoring Algorithm
A New Deterministic RSA-Factoring Algorithm
 
Demystification of vedic multiplication algorithm
Demystification of vedic multiplication algorithmDemystification of vedic multiplication algorithm
Demystification of vedic multiplication algorithm
 

Project PPT slides_student_id#104519347

  • 1. Discrete Transforms & Number Theoretical [06-88-529-1-2016W] A Project Presentation On An efficient binary multiplier design for high speed applications using Karatsuba algorithm and Urdhva- Tiryagbhyam algorithm Instructor : Dr. Huapeng Wu Presented by : Rajan Savaliya (Student ID# 104519325) Savankumar Darji (Student ID# 104519347)
  • 2. Abstract Aim of this research paper is to reduce number of binary multiplication that can save time as well as hardware requirement for implementation of binary multiplier using algorithms like Karatsuba and Urdhva- Tiryagbhyam. To implement binary multiplier, the complexity of design depends on number of multiplication for calculating the product. So, in this paper the main target of author is to reduce number of multiplication with the help of ancient Vedic and classical mathematics.
  • 3. Conventional method of multiplication and its complexity
  • 4. Karatsuba Multiplication This algorithm reduces the number of multiplication comparing to conventional method of multiplication. For example: A 2-digit decimal number can be represented in below convention, a = 10p+q , b = 10r+s Let’s say 87 can be represented as 87 = 10(8)+7 and 56 = 10(5)+6 a = 10(p)+q b = 10(r)+s doing the math by a x b = (10p+q) x (10r+s) we will get a x b = (p x r)100 + ((p x s) + (r x q))10 + (q x s)
  • 5. a x b = (p x r)100 + ((p x s) + (r x q))10 + (q x s) # of multiplication: 1 2 3 4 But if we replace multiplication by several and subtraction we will get this equation: a x b = u x 100 + v x 10 + w Here, u = p x r w = q x s v = (p + q) x (r + s) – u - w These multiplications are called auxiliary multiplications. Here, notice that u, w and v have only 3 multiplication !
  • 6.
  • 7.
  • 9. Block diagram of Karatsuba multiplication
  • 10. 8 digit binary multiplication using Karatsuba Algorithm
  • 11.
  • 13. Complexity of Karatsuba multiplication
  • 14. Total delay required to compute n digit multiplication
  • 15. Urdhva-Tiryagbhyam Multiplication It is the one of the 16 formula which is given in Appendix of Atharvaveda, one of the six Veda from Indian Hinduism. It can compute the N digit multiplication with very fewer and quicker steps when the number of digits are lower i.e. less than 5. The reason behind that is the number of steps for computing multiplication is proportional to the number of digit. For Example: 2 binary digit Multiplication 11 × 11: P0 = 1 × 1 = 1 P1 = (1 × 1) + (1 × 1) + carry_0 = 0 (carry_1 = 1) P2 = (1 × 1) + carry_0 = 0 (carry_1 = 1) Answer = 1001
  • 16. Line representation of the Method: 11 × 11 Calculation for P2 Calculation for P1 Calculation for P1 1 1 1 1 1 1 + carry_0 1 1 1 1 1 1 (1 × 1) + 1 (carry_0) = (1 × 1) + (1 × 1) = (1 × 1) = 1 0 1 0 1 carry_1 Answer = 1 0 0 1
  • 17. Line representation of 4 digit multiplication using Urdhva-Tiryagbhyam Algorithm: • P0 = a0b0 (1 digit) • P1 = LSB{ a1bo+a0b1 } (2 digit) • P2 = LSB{ a2bo+a1b1+a0b2+MSB(P1) } (3 digit) • P3=LSB{ a3bo+a2b1+a1b2+a0b3 +MSB(P2) } (3 digit) • P4=LSB{ a3b1+a2b2+a1b3+MSB(P3) } (3 digit) • P5=LSB{a3b2+a2b3+MSB(P4)}(3 digit) • P6=LSB{a3b3+MSB(P5)} (2 digit) • P7=MSB(P6) (1 digit)
  • 18. Combinational logic circuit of 4 digit binary Urdhva-Tiryagbhyam multiplier :
  • 19. Advantages of the multiplier : Parameters Urdhva- Tiryagbhyam Multiplier Proposed Multiplier Length 8 bits 8 bits Delay 28.27 ns 9.396 ns
  • 20. References 1) “Vedic mathematics”, Swami Sri Bharati Krsna Thirthaji Maharaja, Motilal Banarasidass Indological publishers and Book sellers, 1965. 2) Poornima M, Shivaraj Kumar Patil, Shivukumar , Shridhar K P , Sanjay H, “Implementation of Multiplier using Vedic Algorithm”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), ISSN: 2278-3075, Volume-2, Issue-6, pp. 219-223, May 2013. 3) http://www.stoimen.com/blog/2012/05/15/computer-algorithms- karatsuba-fast-multiplication/ 4) http://www.math.uwaterloo.ca/~anayak/courses/ece103- s10/notes/recursion.pdf 5) http://courses.csail.mit.edu/6.006/spring11/exams/notes3- karatsuba 6) https://class.coursera.org/algo-004/lecture 7) http://courses.csail.mit.edu/6.006/spring11/exams/notes3- karatsuba