Results 261 to 270 of about 7,246 (295)
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2016
Integers are represented on a computer in the form of signed binary numbers. Often 2-, 4- and 8-byte integers are available where a byte possesses eight binary digits. In many computers 4 bytes are the smallest available—addressable—unit of the memory. It may turn out that we can work with one- and 16-byte integers, too.
Gisbert Stoyan, Agnes Baran
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Integers are represented on a computer in the form of signed binary numbers. Often 2-, 4- and 8-byte integers are available where a byte possesses eight binary digits. In many computers 4 bytes are the smallest available—addressable—unit of the memory. It may turn out that we can work with one- and 16-byte integers, too.
Gisbert Stoyan, Agnes Baran
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Parameterised floating-point arithmetic on FPGAs
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002This paper describes the parameterisation, implementation and evaluation of floating-point adders and multipliers for FPGAs. We have developed a method, based on the Handel-C language, for producing technology-independent pipelined designs that allow compile-time parameterisation of design precision and range, and optional inclusion of features such as
Allan Jaenicke, Wayne Luk
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On Local Roundoff Errors in Floating-Point Arithmetic
Journal of the ACM, 1973A bound on the relative error in floating-point addition using a single-precision accumulator with guard digits is derived. It is shown that even with a single guard digit, the accuracy can be almost as good as that using a double-precision accumulator.
Toyohisa Kaneko, Bede Liu
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An IEEE floating point arithmetic implementation
1983 IEEE 6th Symposium on Computer Arithmetic (ARITH), 1983This article describes some of the methods and algorithms used in an implementation of floating point arithmetic following (almost) the IEEE standard defined in (1). The description is more directly algorithm-oriented than the ‘Implementation Guide’ for this standard (2), since the latter does not treat an actual implementation.
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Required scientific floating point arithmetic
1978 IEEE 4th Symposium onomputer Arithmetic (ARITH), 1978Previous papers in computer arithmetic have shown that correct rounded floating point with good arithmetic properties can be attained using guard digits and careful algorithms on the floating point fractions. This paper combines that body of knowledge with proposed exponent forms that are closed with respect to inversion and detection and recovery of ...
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Unum: Adaptive Floating-Point Arithmetic
2016 Euromicro Conference on Digital System Design (DSD), 2016Usually, arithmetic units represent numeric data-types employing fixed-length representations. For instance, hardware representations of real numbers usually employ fixed-length formats defined by the IEEE Standard 754 (32-bit single-precision, 64-bit double-precision, , floating-point numbers).
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Formalization and implementation of floating-point arithmetics
Computing, 1975The paper is intended to show that floating-point arithmetic can be implemented in a way which leads to reasonable mathematical structures as described in chapters 5 and 6. It turns out for instance that all the rules of the minus-operator of the real numbers can be saved and that with respect to ≦ and ≧ inequalities can be manipulated as if they were ...
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2019
You already know about integer arithmetic; now we will introduce some floating-point computations. There is nothing difficult here; a floating-point value has a decimal point in it and zero or more decimals. We have two kinds of floating-point numbers: single precision and double precision.
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You already know about integer arithmetic; now we will introduce some floating-point computations. There is nothing difficult here; a floating-point value has a decimal point in it and zero or more decimals. We have two kinds of floating-point numbers: single precision and double precision.
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Floating point arithmetic and digital filters
IEEE Transactions on Signal Processing, 1992The roundoff noise properties of floating point digital filters are examined. To make the analysis tractable, a high level model to deal with the errors in the inner product operation is developed. This model establishes a broad connection between coefficient sensitivity and roundoff noise.
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Is Floating-Point. Arithmetic Still Adequate?
1988For complicated numerical problems, the error analysis has to be performed by the computer. Several methods for automated error analysis are known. Floating-point arithmetic has to be augmented and programming languages for scientific computation have to be provided (PASCAL-SC and FORTRAN-SC) for that purpose.
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