Comparative Analysis of Multiplications Technique Using Vedic Mathematics Mandeep Singh1, Tarun Chaudhary2 and Balwinder Raj3 1,2 National Institute of Technology Jalandhar,Jalandhar, Punjab, India 3 National Institute of Technical Teachers Training and Research, Chandigarh, India Abstract Vedic mathematics influenced from the ancient arithmetic system of the Vedas makes the regular mathematical calculation at more ease as it can be done by mental approaches. In This paper we are going to presents the concepts and theories behind the Urdhva Tiryagbhyam and Nikhilam Sutra. In this paper, the designs of 4 X4 bits Urdhva Tiryagbhyam, Nikhilam Sutra on kit Spartan 3 XC3S50-5-PQ- 208 have been used. The calculated delay regarding computation for 4X4 Urdhva Tiryagbhyam was 14.14 ns and power is 20.60 mw for Nikhilam Sutra the calculated computational delay is 16.16 ns and total power consumption is 24.60 mw. Keywords1 Vedic mathematics, algorithm, UT, MAC, CIAF, DSP, FFT 1. Introduction The experience of the Multiply and Accumulate (MAC) is the basis for multiplication and in- house products at some of the common computationally intensive Counting Functions (CIAF), which have been used and are currently being used by a lot of Digital signal Processing (DSP) applications, that is, of course, the secret of correspondence, filtration, and industrial applications, in its arithmetic and logic unit, the fast Fourier transform (FFT). This is a must-have for a fast multiplier, since the multiplication is dominated by the time to perform the majority of the DSP algorithms. In order for a certain period of time, the SOUND team, chips, multiplication time is still the most important factor. As a result of the use of the software and processing software, the need for high- speed processing has been increasing. The application of the same type are to be achieved on the basis of the high pass rate of the aerometric activity .One of the significant arithmetic operations such as multiplication and progress, and the rapidmultiplication systems has been an area of interest in the last few decades. Many of the programs in order to reduce the delay and power consumption are very essential requirements. In a digital circuit design, as it is most commonly used ingredients is the digital opinion leaders. They are used to carry out a transaction, such as they are, is the fastest, most reliable, and most efficient components. Today, many of the algorithms of features, multiplication, and each one offers different benefits and trade-offs in terms of energy, speed, circuit complexity, and in the field. The most important components in many digital signal processors (DSP), it is called a digital multiplier, and the rate of their multipliers is determined by the speed of the DSP. The matrix multiplication algorithm and a Box, the multiplication algorithms are two of the most commonly used property of multiplication algorithms, which are used in the field of digital computer hardware. For the moment, to carry out the calculations with the use of the array multiplier is relatively small, since these are calculated, regardless of their parallel ones. The amount of time that it takes to multiply by International Conference on Emerging Technologies: AI, IoT, and CPS for Science & Technology Applications, September 06–07, 2021, NITTTR Chandigarh, India EMAIL: mandeep.moni.singh@gmail.com (A. 1); chaudharyt@nitj.ac.in (A. 2); balwinderraj@gmail.com (A. 3) ORCID: 0000-0002-4577-2675 (A. 1); 0000-0003-1854-4535 (A. 2); 0000-0002-3065-6313 (A. 3) ©2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org) the front door is visible from the windows of the multiplication of series, which is called the grip. For high-speed multiplication, the use of large booth, chains, and a big one at that, is registered for a certain amount, and the relocation will require an exponentialoperation. In this article, we are going to discuss about two methods that Nikhilam Sutra Urdhva tiryagbhyam (at output), the binary number system has got itself first applied with the sutras and the system is used for the development of the different digital devices. 1.1 Need for Vedic mathematics 1. It lessens the scratch from finger. 2. It consumes the less time. 3. An influential tool regarding calculation. 4. Solution is presented in a single line. 5. Better work force. 1.2 Applications of multiplier Multipliers are widely used in 1. For convolutions, factorial calculations. 2. Arithmetic and logic unit in processors 3. For various mathematical operationslike rooting, Divisions 4. Floating point units 5. FIR filters 6. Speech synthesis/recognition 7. DSP algorithms such as FFT DFT 8. Math processor 9. In cryptography 2. Vedic multiplication Algorithms The Vedic multiplier focused in this work is leaned on the formula of Vedic multiplication which are sutras. The sutras find their usage in the decimal number multiplication. 2.1. Urdhva Tiryagbhyam sutra Urdhva Tiryagbhyam multiplier is actually an algorithm of Vedic mathematics discovered in India during the Vedic era. If we tell about the sutras, it is a formula and related to multiplier mainly “vertical and crosswise” .Here the partial product generatedand concluded with the partial product of concurrent addition Figure 1: General formula for Vedic multiplications Example 46 X 43 1978 2.2. Nikhliam sutra Multiplication for the base 10 numbers are performed by Nikhliam Sutra (e.g.: 97 x 94 or 103 x 105). Sample (i):- Numbers (2 no) < Base. 97 3 X 94 6 9118 Sample (ii):- Numbers (2 no) > Base. 104 4 X 105 5 1 0, 9 2 0 Sample (iii):- One number lower and other one higher than the base. 103 3 X 98 -2 1 0, 0 9 4 3. Simulations and results The Urdwa Sutra, Nikhliam Sutra can be implementing on the Xilinx 8.1 and family used SPARTAN 3 and device XC3S50E the synthesis report for HDL is shown in Table 1. The output waveform of 4x4 urdhwa sutra is shown in Figure 2. In this case apply data in the form of bits and output is displayed at the end of y (output). The output waveform of 4x4 nikhilam sutra is shown in Figure 3. In this case apply data in the form of bits and output is displayed at the end of y (output). Table 1 HDL Synthesis Report Device Spartan 3XC3S50- 4x4 Urdwa Sutra 4x4 NIKHLIAM 5-PQ-208 SUTRA Delay 14.14ns 16.16ns Power consumptions 20.60mw 24.62mw Number of slices 23 out of 768 16 out of 2448 ( 2% ) ( 1% ) Number of inputs LUT 40 out of 1536 29 out of 4896 ( 2 %) (1%) Number of bonded IOBs 17 out of 146 16 out of 152 (11%) ( 10% ) Figure 2: Waveform for 4 x 4 urdhva sutra Figure 3: Waveform for Nikhilam sutra 4. Conclusions The designs of 4 X4 bits Urdhva Tiryagbhyam, Nikhilam Sutra have been implemented on Spartan XC2S50E-5-PQ-208. The computation delay for 4X4 Urdhva Tiryagbhyam was 14.14 ns and power is 20.60 mw. For Nikhilam Sutra the computational delay is 16.16 ns and power consumption is 24.60 mw. So from above results the Urdhva Tiryagbhyam has best sutra because it occupies the less delay and power consumptions. 5. References 1. K. Roy and S. C. Prasad, “Low-Power CMOS VLSI Circuit Design”, John Wiley & Sons, 1999. 2. A. P. Chandrakasan and W. 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