Table-free Seed Generation for Hardware Newton–Raphson Square Root and Inverse Square Root Implementations in IoT Devices

Author(s):  
Luis Parrilla ◽  
Antonio Lloris ◽  
Encarnacion Castillo ◽  
Antonio Garcia
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Gayathri R. Prabhu ◽  
Bibin Johnson ◽  
J. Sheeba Rani

A Givens rotation based scalable QRD core which utilizes an efficient pipelined and unfolded 2D multiply and accumulate (MAC) based systolic array architecture with dynamic partial reconfiguration (DPR) capability is proposed. The square root and inverse square root operations in the Givens rotation algorithm are handled using a modified look-up table (LUT) based Newton-Raphson method, thereby reducing the area by 71% and latency by 50% while operating at a frequency 49% higher than the existing boundary cell architectures. The proposed architecture is implemented on Xilinx Virtex-6 FPGA for any real matrices of sizem×n, where4≤n≤8andm≥nby dynamically inserting or removing the partial modules. The evaluation results demonstrate a significant reduction in latency, area, and power as compared to other existing architectures. The functionality of the proposed core is evaluated for a variable length adaptive equalizer.


Computing ◽  
1991 ◽  
Vol 46 (1) ◽  
pp. 67-86 ◽  
Author(s):  
P. Montuschi ◽  
M. Mezzalama

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1622
Author(s):  
Feibao Xiao ◽  
Feng Liang ◽  
Bin Wu ◽  
Junzhe Liang ◽  
Shuting Cheng ◽  
...  

As a substitute for the IEEE 754-2008 floating-point standard, Posit, a new kind of number system for floating-point numbers, was put forward recently. Hitherto, some studies have proven that Posit is a better floating-point style than IEEE 754-2008 in some fields. However, most of these studies presented the advantages of Posit from the arithmetical aspect, but none of them suggested it had a better hardware implementation than that of IEEE 754-2008. In this paper, we propose several hardware implementations that contain the Posit adder/subtractor, multiplier, divider, and square root. Our goal is to achieve an arbitrary Posit format and exploit the minimum circuit area, which is required in embedded devices. To implement the minimum circuit area for the divider and square root, the alternating addition and subtraction method is used rather than the Newton–Raphson method. Compared with other works, the area of our divider is about 0.2×–0.7× (FPGA). Furthermore, this paper provides the synthesis results for each critical module with the Xilinx Virtex-7 FPGA VC709 platform.


Computation ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 41 ◽  
Author(s):  
Cezary J. Walczyk ◽  
Leonid V. Moroz ◽  
Jan L. Cieśliński

We present a new algorithm for the approximate evaluation of the inverse square root for single-precision floating-point numbers. This is a modification of the famous fast inverse square root code. We use the same “magic constant” to compute the seed solution, but then, we apply Newton–Raphson corrections with modified coefficients. As compared to the original fast inverse square root code, the new algorithm is two-times more accurate in the case of one Newton–Raphson correction and almost seven-times more accurate in the case of two corrections. We discuss relative errors within our analytical approach and perform numerical tests of our algorithm for all numbers of the type float.


2021 ◽  
Vol 1 (2) ◽  
pp. 1-30
Author(s):  
William B. Langdon ◽  
Oliver Krauss

We use continuous optimisation and manual code changes to evolve up to 1024 Newton-Raphson numerical values embedded in an open source GNU C library glibc square root sqrt to implement a double precision cube root routine cbrt, binary logarithm log2 and reciprocal square root function for C in seconds. The GI inverted square root x -1/2 is far more accurate than Quake’s InvSqrt, Quare root. GI shows potential for automatically creating mobile or low resource mote smart dust bespoke custom mathematical libraries with new functionality.


Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 86
Author(s):  
Cezary J. Walczyk ◽  
Leonid V. Moroz ◽  
Jan L. Cieśliński

Direct computation of functions using low-complexity algorithms can be applied both for hardware constraints and in systems where storage capacity is a challenge for processing a large volume of data. We present improved algorithms for fast calculation of the inverse square root function for single-precision and double-precision floating-point numbers. Higher precision is also discussed. Our approach consists in minimizing maximal errors by finding optimal magic constants and modifying the Newton–Raphson coefficients. The obtained algorithms are much more accurate than the original fast inverse square root algorithm and have similar very low computational costs.


Author(s):  
Cezary J. Walczyk ◽  
Leonid V. Moroz ◽  
Jan L. Cieśliński

We present an improved algorithm for fast calculation of the inverse square root for single-precision floating-point numbers. The algorithm is much more accurate than the famous fast inverse square root algorithm and has a similar computational cost. The presented modification concern Newton-Raphson corrections and can be applied when the distribution of these corrections is not symmetric (for instance, in our case they are always negative).


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