11 research outputs found

    Vedic-Based Squarers with High Performance

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    Squaring operation represents a vital operation in various applications involving image processing, rectangular to polar coordinate conversion, and many other applications. For its importance, a novel design for a 6-bit squarer basing on the Vedic multiplier (VM) is offered in this work. The squarer design utilizes dedicated 3-bit squarer modules, a (3*3) VM, and an improved Brent-Kung Carry-Select Adder (IBK-CSLA) with the amended design of XOR gate to perform fast partial-products addition. The 6-bit squarer circuit can readily be expanded for larger sizes such as 12-bit and 24-bit numbers which are useful for squaring the mantissa part of  32-bit floating-point numbers. The paper also offers three architectures for 24- bit squarer using pipelining concept used in various stages. All these squaring circuits are designed in VHDL and implemented by Xilinx ISE13.2 and FPGA. The synthesis results reveal that the offered 6-bit, 12- bit, and 24- bit squarer circuits introduce eminent outcomes in terms of delay and area when utilizing IBK-CSLA with amended XOR gate. Also, it is found that the three architectures of 24- bit squarer present dissimilar delay and area, and the architecture design based on 3-bit squarer modules with  (3*3) VM introduces the lowest area and delay

    Efficient FPGA Based Matrix Multiplication Using Mux and Vedic Multiplier

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    Most of the algorithms which are used in DSP, image and video processing, computer graphics, vision and high performance supercomputing applications require multiplication and matrix operation as the kernel operation. In this paper, we propose Efficient FPGA based matrix multiplication using MUX and Vedic multiplier. The 2x2, 3x2 and 3x3 MUX based multipliers are designed. The basic lower order MUX based multipliers are used to design higher order MxN multipliers with a concept of UrdhvaTiryakbyham Vedic approach. The proposed multiplier is used for image processing applications. It is observed that the device utilization and combinational delay are less in the proposed architecture compared to existing architectures

    Adaptive and hybrid schemes for efficient parallel squaring and cubing units

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    Squaring (X2) and cubing (X3) units are special operations of multiplication used in many applications, such as image compression, equalization, decoding and demodulation, 3D graphics, scientific computing, artificial neural networks, logarithmic number system, and multimedia application. They can also be an efficient way to compute other basic functions. Therefore, improving their performances is a goal for many researchers. This dissertation will discuss modification to algorithms to compute parallel squaring and cubing units in both signed and unsigned representation. After that, truncated technique is applied to improve their performance. Each unit is modeled and estimated to obtain its area, delay by using linear evaluation model. A C program was written to generate Hardware Description Language files for each unit. These units are simulated and verified in simulation. Moreover, area, delay, and power consumption are calculated for each unit and compared with those ones in previous approaches for both Virtex 5 Xilinx FPGA and IBM 65nm ASIC technologies

    2010 Annual Research Symposium Abstract Book

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    2010 annual volume of abstracts for science research projects conducted by students at Trinity College
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