Floating-Point Representation, Algorithms, and Implementations

Ercegovac, M.D.

doi:10.1016/b978-155860798-9/50010-5

Cited by 2 publications

(2 citation statements)

References 77 publications

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“…First, the operands may be swapped, as shown in Figure 2, so that A N is the operand with the larger exponent in the rest of the circuit. This is similar to a technique used in BFP addition [20]. Also, the effective operation (EOP) is computed, based on the input operation (OP) and the signs of the operands, A sign and B sign , as EOP = OP xor A sign xor B sign , where OP is zero for addition and one for subtraction.…”

Section: Bid Addition/subtraction Algorithmmentioning

confidence: 99%

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Hardware design of a Binary Integer Decimal-based floating-point adder

Tsen

González-Navarro

Schulte³

2007

2007 25th International Conference on Computer Design

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Because of the growing importance of decimal floating-point (DFP) arithmetic, specifications for it are included in the IEEE Draft Standard for Floating-point Arithmetic (IEEE P754). In this paper, we present a novel algorithm and hardware design for a DFP adder. The adder performs addition and subtraction on 64-bit operands that use the IEEE P754 binary encoding of DFP numbers, widely known as the Binary Integer Decimal (BID) encoding. The BID adder uses a novel hardware component for decimal digit counting and an enhanced version of a previously published BID rounding unit. By adding more sophisticated control, operations are performed with variable latency to optimize for common cases. We show that a BID-based DFP adder design can be achieved with a modest area increase compared to a single 2-stage pipelined 64-bit fixed-point multiplier. Over 70% of the BID adder's area is due the 64-bit fixed-point multiplier, which can be shared with a binary floating-point multiplier and hardware for other DFP operations. To our knowledge, this is the first hardware design for adding and subtracting IEEE P754 BID-encoded DFP numbers.

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Section: Bid Addition/subtraction Algorithmmentioning

confidence: 99%

“…As a potential technique for implementing BID addition in the decimal64 format with p = 16, consider the addition of A N = 1,234,567,890,123,456 × 10 17 [20], and many processors include a 64-bit by 64-bit multiplier. With a rounder of this size, we divide the problem space into three cases.…”

Section: Bid Addition/subtraction Techniquementioning

confidence: 99%

Hardware design of a Binary Integer Decimal-based floating-point adder

Tsen

González-Navarro

Schulte³

2007

2007 25th International Conference on Computer Design

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A ten time smaller version of CPC global daily precipitation dataset for parallel distributed processing in Matlab and R

N.,

2024

Rom. Rep. Phys.

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A ten times smaller version of CPC Global Unified Gauge-Based Daily Precipitation Dataset (1979–2021) is released and described in this paper. Its usability is tested and proved, firstly, by illustrating that the transition to the derived smaller dataset is a case of Pearson correlation transitivity starting with the scale of global yearly data and, secondly, by using the original correlation performance criterion that the original dataset satisfies relative to the set of global actual measurements on the record. Subsequently, the daily, weekly, and monthly data cases are considered and discussed. The dataset is (re)structured for parallel processing in Matlab and R from the level of global daily data. Considering the above arguments and its reduced size, the derived dataset is appropriate to be used with Matlab and R as a replacement for the original dataset, especially for the case when much faster exploratory master-slave parallel and distributed Matlab and/or R tasks will run over locally distributed data on the slaves.

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Floating-Point Representation, Algorithms, and Implementations

Cited by 2 publications

References 77 publications

Hardware design of a Binary Integer Decimal-based floating-point adder

Hardware design of a Binary Integer Decimal-based floating-point adder

A ten time smaller version of CPC global daily precipitation dataset for parallel distributed processing in Matlab and R

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