A high-speech 32 bit IEEE floating-point chip set for digital signal processing

Author(s):  
Bob Woo ◽  
Lyon Lin ◽  
F. Ware
2020 ◽  
Vol 38 (02) ◽  
Author(s):  
PHAM TRAN BICH THUAN

At present, floating-point operations are used as add-on functions in critical embedded systems, such as physics, aerospace system, nuclear simulation, image and digital signal processing, automatic control system and optimal control and financial, etc. However, floating-point division is slower than floating-point multiplication. To solve this problem, many existing works try to reduce the required number of iterations, which exploit large Look Up Table (LUT) resource to achieve approximate mantissa of a quotient. In this paper, we propose a novel prediction algorithm to achieve an optimal quotient by predicting certain bits in a dividend and a divisor, which reduces the required LUT resource. Therefore, the final quotient is achieved by accumulating all predicted quotients using our proposed prediction algorithm. The experimental results show that only 3 to 5 iterations are required to obtain the final quotient in a floating-point division computation. In addition, our proposed design takes up 0.84% to 3.28% (1732 LUTs to 6798 LUTs) and 5.04% to 10.08% (1916 (ALUT) to 3832 (ALUT)) when ported to Xilinx Virtex-5 and Altera Stratix-III FPGAs, respectively. Furthermore, our proposed design allows users to track remainders and to set customized thresholds of these remainders to be compatible with a specific application.


Author(s):  
Kishan Maladkar

A Floating Point Unit is a math co-processor that is in the most demand of Digital Signal Processing (DSP), Processors and more. It is used to perform functions or operations on floating point numbers like addition, subtraction, multiplication, division, square root and more. It is specifically designed to carry out mathematical operations and it can be emulated in CPU. Floating point unit is a common operation used in advanced Digital Signal Processing and various processor applications. The aim was to develop an optimized floating point unit so that the delay was reduced and efficiency was increased. The floating point unit has been written according to IEEE 754 standard and the entire design has been coded in Verilog HDL. The results are improved by 12% with the usage of Vedic multiplier that is a delay of 4.450ns as compared to 5.123ns with an array multiplier. Designs can be further optimized using low power designing techniques at architectural level. Different behaviour can be observed for different size and technologies.


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