Division and extraction operation processor and operation processing system for Point floating-point numbers

Abstract

The invention provides a division and extraction operation processor and an operation processing system for Posit floating-point numbers, and relates to the technical field of computers. An operationprocessing system for performing addition and subtraction alternate operation by utilizing intermediate data of a complement type to finish division and extraction operation of Point floating-point numbers is creatively created. The division and extraction operation processing system for the Posit floating-point number comprises a CPU, a decoding circuit, a coding circuit, a division and extraction operation processor for the Posit floating-point number. The CPU is a central processing unit of the computer; connection with the decoding circuit, and the Point floating-point number division andextraction operation processor is connected with the encoding circuit and is used for performing the target operation by the intermediate data in the complement form to obtain an operation result expressed by the intermediate data in the complement form and sending the operation result expressed by the intermediate data in the complement form to the encoding circuit.

Description

technical field [0001] The application relates to the field of computer technology, in particular to a Posit floating-point number division and square root arithmetic processor and an arithmetic processing system. Background technique [0002] Floating-point numbers are a commonly used data representation method in the field of scientific computing and high-performance computing. In particular, floating-point numbers are widely used for data processing when the accuracy of calculation results is required to be high, such as in the fields of automatic driving, aerospace, and mechanical computing. . [0003] Posit standard floating-point numbers are more flexible than IEEE 754 standard floating-point numbers, and the sampling distribution of Posit floating-point numbers on real numbers is related to the sigmoid function, and the sigmoid function is a commonly used activation function in machine learning, so Using Posit floating-point numbers for machine learning, the efficien...

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Problems solved by technology

[0004] The current method for processing Posit floating-point numbers is usually to use a decoding circuit to convert the Posit floating-point numbers participating in the calculation into the original code, and input the original code to the calculation circuit for calculation. Whether the number of points is a negative number, and then unify the original code of the negative Posit floating point number into the form of complement code, and then convert the operation result of the form of complement code into the original code after obtaining the operation result of the complement code form. The entire operation process needs to be repeated Convert the original code to the complement code, and the complement code to the original code, and it is necessary to judge the positive or negative of the Posit floating-point number at each operation node, which makes the entire operation logic of the Posit floating-point number very complicated and cumbersome, resulting in the circuit of the operation circuit The area is too large

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