Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a smal...

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Veröffentlicht in:	Electronics Jg. 11; H. 15; S. 2285
Hauptverfasser:	Kusaka, Takashi, Tanaka, Takayuki
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 22.07.2022
Schlagworte:	algorithm design and analysis Algorithms Approximation arctangent approximation arctangent approximation; trigonometric functions approximation; elemental function approximation; fused multiply–add; algorithm design and analysis; computational cost reduction Attitude control Compilers Computation computational cost reduction Digital signal processors elemental function approximation Embedded systems Field programmable gate arrays Floating point arithmetic fused multiply-add Graphics processing units Machine learning Mathematical analysis Microcontrollers Multiplication & division Performance evaluation Power consumption Power management Robot control Signal processing Trigonometric functions trigonometric functions approximation
ISSN:	2079-9292, 2079-9292
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Abstract	In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a small number of computation cycles, which may be useful when embedded in a field-programmable gate array (FPGA) or micro controller unit (MCU), or when performing many large-scale operations on a graphics processing unit (GPU). It is necessary to devise algorithms to obtain the desired calculated values without an accelerator or compiler assistance. The residual correction method (RCM) developed here can produce simple and accurate approximations of certain nonlinear functions with minimal multiply–add operations. In this study, we designed an algorithm for the approximate computation of trigonometric and inverse trigonometric functions, which are nonlinear elementary functions, to achieve their fast and accurate computation. A fast first approximation and a more accurate second approximation of each function were created using RCM with a less than 0.001 error using multiply–add operations only. This achievement is particularly useful for MCUs, which have a low power consumption but limited computational power, and the proposed approximations are candidate algorithms that can be used to stabilize the attitude control of robots and drones, which require real-time processing.
AbstractList	In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a small number of computation cycles, which may be useful when embedded in a field-programmable gate array (FPGA) or micro controller unit (MCU), or when performing many large-scale operations on a graphics processing unit (GPU). It is necessary to devise algorithms to obtain the desired calculated values without an accelerator or compiler assistance. The residual correction method (RCM) developed here can produce simple and accurate approximations of certain nonlinear functions with minimal multiply–add operations. In this study, we designed an algorithm for the approximate computation of trigonometric and inverse trigonometric functions, which are nonlinear elementary functions, to achieve their fast and accurate computation. A fast first approximation and a more accurate second approximation of each function were created using RCM with a less than 0.001 error using multiply–add operations only. This achievement is particularly useful for MCUs, which have a low power consumption but limited computational power, and the proposed approximations are candidate algorithms that can be used to stabilize the attitude control of robots and drones, which require real-time processing.
Author	Takayuki Tanaka Takashi Kusaka
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SubjectTerms	algorithm design and analysis Algorithms Approximation arctangent approximation arctangent approximation; trigonometric functions approximation; elemental function approximation; fused multiply–add; algorithm design and analysis; computational cost reduction Attitude control Compilers Computation computational cost reduction Digital signal processors elemental function approximation Embedded systems Field programmable gate arrays Floating point arithmetic fused multiply-add Graphics processing units Machine learning Mathematical analysis Microcontrollers Multiplication & division Performance evaluation Power consumption Power management Robot control Signal processing Trigonometric functions trigonometric functions approximation
Title	Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers
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