Results 241 to 250 of about 70,095 (287)
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Roundings in floating point arithmetic
1972 IEEE 2nd Symposium on Computer Arithmetic (ARITH), 1972In this paper we discuss directed roundings and indicate how hardware might be designed to produce proper upward-directed, downward-directed, and certain commonly used symmetric roundings. Algorithms for the four binary arithmetic operations and for rounding are presented, together with proofs of their correctness; appropriate formulas for a priori ...
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Journal of the ACM, 1960
Three types of floating-point arithmetics with error control are discussed and compared with conventional floating-point arithmetic. General multiplication and division shift criteria are derived (for any base) for Metropolis-type arithmetics. The limitations and most suitable range of application for each arithmetic are discussed.
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Three types of floating-point arithmetics with error control are discussed and compared with conventional floating-point arithmetic. General multiplication and division shift criteria are derived (for any base) for Metropolis-type arithmetics. The limitations and most suitable range of application for each arithmetic are discussed.
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Arithmetic Coding for Floating-Point Numbers
2021 IEEE Conference on Dependable and Secure Computing (DSC), 2021To enable the usage of standard hardware in safety-critical applications for production systems, new approaches for hardware fault tolerance are required. These approaches must be implemented on software level. As shown in the literature, arithmetic coding is a promising approach, but only supports integer calculations.
Marc Fischer +3 more
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Microprocessors and Microsystems, 1979
So far all the binary numbers considered have been integers with a maximum of 16 bits. Thus it has only been possible to represent numbers in the range Open image in new window or Open image in new ...
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So far all the binary numbers considered have been integers with a maximum of 16 bits. Thus it has only been possible to represent numbers in the range Open image in new window or Open image in new ...
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Axiomatizations of floating point arithmetics
1985 IEEE 7th Symposium on Computer Arithmetic (ARITH), 1985We present a universal scheme for axiomatizing floating point ariththmetic. The schema can be used to axiomatize any floating point arithmetic. It consists of a labeled graph with vertices describing some arithmetical properties and edges containing appropriate axioms. The language of floating point arithmetic is developed gradually in this scheme. The
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Floating-point on-line arithmetic: Algorithms
1981 IEEE 5th Symposium on Computer Arithmetic (ARITH), 1981For effective application of on-line arithmetic to practical numerical problems, floating-point algorithms for on-line addition/subtraction and multiplication have been implemented by introducing the notion of quasi-normalization. Those proposed are normalized fixed-precision FLPOL (floating-point on-line) algorithms.
Osaaki Watanuki, Milos D. Ercegovac
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Floating Point Arithmetic in Future Supercomputers
The International Journal of Supercomputing Applications, 1989Considerations in the floating-point design of a supercomputer are discussed. Particular attention is given to word size, hardware support for extended precision, format, and accuracy characteristics. These issues are discussed from the perspective of the Numerical Aerodynamic Simulation Systems Division at NASA Ames.
David H. Bailey +3 more
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2012
There are many data processing applications (e.g. image and voice processing), which use a large range of values and that need a relatively high precision. In such cases, instead of encoding the information in the form of integers or fixed-point numbers, an alternative solution is a floating-point representation.
Jean-Pierre Deschamps +2 more
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There are many data processing applications (e.g. image and voice processing), which use a large range of values and that need a relatively high precision. In such cases, instead of encoding the information in the form of integers or fixed-point numbers, an alternative solution is a floating-point representation.
Jean-Pierre Deschamps +2 more
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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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