State Reference Computation for PMSM Implemented with Single-Precision Floating Point Datatype

2020 ◽  
Author(s):  
Oliver Dieterle ◽  
Thomas Greiner ◽  
Peter Heidrich
Keyword(s):  
Floating Point ◽  
Single Precision ◽  
State Reference

scholarly journals Research on IEEE 754 Standard Single Precision Floating Point Multipliers Designed using Urdhva Triyagbhyam Sutra of Vedic Mathematics

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2990-2993
Keyword(s):  
Floating Point ◽  
Double Precision ◽  
Single Precision ◽  
Vedic Mathematics ◽  
Quadruple Precision

Duplication of the coasting element numbers is the big activity in automated signal handling. So the exhibition of drifting problem multipliers count on a primary undertaking in any computerized plan. Coasting factor numbers are spoken to utilizing IEEE 754 modern day in single precision(32-bits), Double precision(sixty four-bits) and Quadruple precision(128-bits) organizations. Augmentation of those coasting component numbers can be completed via using Vedic generation. Vedic arithmetic encompass sixteen wonderful calculations or Sutras. Urdhva Triyagbhyam Sutra is most usually applied for growth of twofold numbers. This paper indicates the compare of tough work finished via exceptional specialists in the direction of the plan of IEEE 754 ultra-modern-day unmarried accuracy skimming thing multiplier the usage of Vedic technological statistics.

scholarly journals NULL Convention Floating Point Multiplier

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Anitha Juliette Albert ◽  
Seshasayanan Ramachandran
Keyword(s):  
High Precision ◽  
Dynamic Range ◽  
Digital Signal ◽  
High Dynamic Range ◽  
Floating Point ◽  
Single Precision ◽  
Critical Part ◽  
Point Multiplication ◽  
Null Convention Logic ◽  
High Dynamic

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.

The FPGA Implementation of Single-Precision Floating-Point Adder

2014 ◽  
Vol 1008-1009 ◽  
pp. 668-671
Author(s):  
Hai Ke Liu ◽  
Xin Gna Kang ◽  
Shun Wang
Keyword(s):  
Real Number ◽  
Fpga Implementation ◽  
Floating Point ◽  
Single Precision ◽  
Operation Process ◽  
Storage Format ◽  
Process Ability

A design of single precision floating point adder based on FPGA is presented,by analysing the form of real number formed on IEEE 754 and the storage format of IEEE 754 single-precision floating point,the addition arithmetic process which is easy to realized by using FPGA is put forward,the split of module based on the arithmetic process facilitates the realization of pipeline designing,so the single precision floating point adder introduce by this paper has powerful operation process ability.

Operational Single-Precision Earth-System Modelling at ECMWF

2021 ◽  
Author(s):  
Sam Hatfield ◽  
Kristian Mogensen ◽  
Peter Dueben ◽  
Nils Wedi ◽  
Michail Diamantakis
Keyword(s):  
Atmospheric Model ◽  
Floating Point ◽  
System Modelling ◽  
Double Precision ◽  
Earth System ◽  
Single Precision ◽  
System Models ◽  
Floating Point Arithmetic ◽  
Point Arithmetic ◽  
Earth System Models

<p>Earth-System models traditionally use double-precision, 64 bit floating-point numbers to perform arithmetic. According to orthodoxy, we must use such a relatively high level of precision in order to minimise the potential impact of rounding errors on the physical fidelity of the model. However, given the inherently imperfect formulation of our models, and the computational benefits of lower precision arithmetic, we must question this orthodoxy. At ECMWF, a single-precision, 32 bit variant of the atmospheric model IFS has been undergoing rigorous testing in preparation for operations for around 5 years. The single-precision simulations have been found to have effectively the same forecast skill as the double-precision simulations while finishing in 40% less time, thanks to the memory and cache benefits of single-precision numbers. Following these positive results, other modelling groups are now also considering single-precision as a way to accelerate their simulations.</p><p>In this presentation I will present the rationale behind the move to lower-precision floating-point arithmetic and up-to-date results from the single-precision atmospheric model at ECMWF, which will be operational imminently. I will then provide an update on the development of the single-precision ocean component at ECMWF, based on the NEMO ocean model, including a verification of quarter-degree simulations. I will also present new results from running ECMWF's coupled atmosphere-ocean-sea-ice-wave forecasting system entirely with single-precision. Finally I will discuss the feasibility of even lower levels of precision, like half-precision, which are now becoming available through GPU- and ARM-based systems such as Summit and Fugaku, respectively. The use of reduced-precision floating-point arithmetic will be an essential consideration for developing high-resolution, storm-resolving Earth-System models.</p>

COMPUTING LINE INTERSECTIONS

2001 ◽  
Vol 01 (02) ◽  
pp. 217-230 ◽  
Author(s):  
M. GAVRILOVA ◽  
J. ROKNE
Keyword(s):  
Intersection Point ◽  
Binary Search ◽  
Floating Point ◽  
Search Procedure ◽  
Single Precision ◽  
Exact Arithmetic ◽  
The Core ◽  
Speed Up ◽  
Computationally Expensive ◽  
Floating Point Numbers

The main result of the paper is a new and efficient algorithm to compute the closest possible representable intersection point between two lines in the plane. The coordinates of the points that define the lines are given as single precision floating-point numbers. The novelty of the algorithm is the method for deriving the best possible representable floating point numbers: instead of solving the equations to compute the line intersection coordinates exactly, which is a computationally expensive procedure, an iterative binary search procedure is applied. When the required precision is achieved, the algorithm stops. Only exact comparison tests are needed. Interval arithmetic is applied to further speed up the process. Experimental results demonstrate that the proposed algorithm is on the average ten times faster than an implementation of the line intersection computation subroutine using the CORE library exact arithmetic.

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