scholarly journals Floating Point Multiplication Based on Schonhage Strassen Algorithm

2018 ◽  
Vol 7 (2.20) ◽  
pp. 14
Author(s):  
B Srikanth ◽  
M Siva Kumar ◽  
K Hari Kishore

In this paper, the single precision float point multiplication is performed using the Schonhage Strassen Algorithm. There are several types of floating point multiplications like Karatsubha and Toom cook. The Schonhage Strassen algorithm is conventionally a fixed point integer multiplication algorithm. The main advantage of the Schonhage Strassen multiplication is that, the multiplication of integer values greater than 5 digits ranging from 2215 to 2217 bit values proves to be efficient. The validation of the proposed floating point multiplication is done using FPGA real time implementation. The analysis of parameters like area and power are evaluated.  

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Anitha Juliette Albert ◽  
Seshasayanan Ramachandran

Floating point multiplication is a critical part in high dynamic range and computational intensive digital signal processing applications which require high precision and low power. This paper presents the design of an IEEE 754 single precision floating point multiplier using asynchronous NULL convention logic paradigm. Rounding has not been implemented to suit high precision applications. The novelty of the research is that it is the first ever NULL convention logic multiplier, designed to perform floating point multiplication. The proposed multiplier offers substantial decrease in power consumption when compared with its synchronous version. Performance attributes of the NULL convention logic floating point multiplier, obtained from Xilinx simulation and Cadence, are compared with its equivalent synchronous implementation.


2014 ◽  
Vol 687-691 ◽  
pp. 3494-3497
Author(s):  
Wei Sun ◽  
Jun She An ◽  
Shuang Yang

Sequence detection is used in many algorithms and applications. Sequences are different depending on different demands. In the process of floating-point CORDIC coprocessor design,data are need to change from floating point format to fixed point format. This process is necessary to detect the number of consecutive zeros. We design the leading-zero-counting algorithm to achieve this function, and this conversion process is completed in a very fixed short time, to ensure the needs of the floating point CORDIC coprocessor.


Currently, each CPU has one or additional Floating Point Units (FPUs) integrated inside it. It is usually utilized in math wide-ranging applications, such as digital signal processing. It is found in places be established in engineering, medical and military fields in adding along to in different fields requiring audio, image or video handling. A high-speed and energy-efficient floating point unit is naturally needed in the electronics diligence as an arithmetic unit in microprocessors. The most operations accounting 95% of conformist FPU are multiplication and addition. Many applications need the speedy execution of arithmetic operations. In the existing system, the FPM(Floating Point Multiplication) and FPA(Floating Point Addition) have more delay and fewer speed and fewer throughput. The demand for high speed and throughput intended to design the multiplier and adder blocks within the FPM (Floating point multiplication)and FPA(Floating Point Addition) in a format of single precision floating point and double-precision floating point operation is internally pipelined to achieve high throughput and these are supported by the IEEE 754 standard floating point representations. This is designed with the Verilog code using Xilinx ISE 14.5 software tool is employed to code and verify the ensuing waveforms of the designed code


Currently in the real-time audio applications fixed point CODEC is being used. But the major disadvantage of such CODEC is the speed and accuracy. Because , as the DSP systems cannot be operated with real-time signal ‘t’, but they can be operated with the discrete time ‘n’ , the real-time analog signal x(t) is to be converted into discrete time signal x(n) by the analog to digital convert (ADC). The most widely used ADC in the signal processing environment is sigma-delta ADC. But, it can operate with the maximum speed of 1MHz. The DSP processor can give several times more speed than sigma-delta ADC. Hence, the speed of DSP system is being limited by sigma-delta ADC, even though the DSP system has the capability to operate with great speed. Similarly, the accuracy is being missed because the floating point samples are converted into fixed point to get the compatibility with fixed point DSP processor. To eliminate these two bottlenecks the novel design methodology has been proposed in which the ADC and DAC have been eliminated and the system is developed by the 16 bit floating point.


2019 ◽  
Vol 8 (2S3) ◽  
pp. 1064-1067

Multiplication of floating point(FP) numbers is greatly significant in many DSP applications. The performance of the DSP’s is substantially decided by the speed of the multipliers used. This paper proposes the design and implementation of IEEE 754 standard single precision FP multiplier using Verilog, synthesized and simulated in Xilinx ISE10.1. Urdhva Triyagbhyam Sutra of Vedic mathematics is used for the unsigned mantissa calculation. The design implements floating point multiplication with sign bit and exponent calculations. The proposed design is achieved high speed with minimum delay of 3.997ns.Multiplication of floating point(FP) numbers is greatly significant in many DSP applications. The performance of the DSP’s is substantially decided by the speed of the multipliers used. This paper proposes the design and implementation of IEEE 754 standard single precision FP multiplier using Verilog, synthesized and simulated in Xilinx ISE10.1. Urdhva Triyagbhyam Sutra of Vedic mathematics is used for the unsigned mantissa calculation. The design implements floating point multiplication with sign bit and exponent calculations. The proposed design is achieved high speed with minimum delay of 3.997ns.


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