TY - GEN
T1 - Fused floating-point arithmetic for DSP
AU - Swartzlander, Earl E.
AU - Saleh, Hani H.
PY - 2008
Y1 - 2008
N2 - This paper extends the consideration of fused floating-point arithmetic to operations that are frequently encountered in DSP. The Fast Fourier Transform is a case in point, it uses a complex butterfly operation. For a radix-2 implementation, the butterfly consists of a complex multiply followed by the complex addition and subtraction of the same pair of data. These butterfly operations can be implemented with two fused primitives, a fused two-term inner product and a fused add subtract unit. A floating-point fused FFT Butterfly unit is presented that performs single-precision butterfly floating-point operation in a time that is only 87% the time required for a conventional floating-point butterfly. When placed and routed in a 45nm process, the fused FFT Butterfly unit occupied about 72% of the area needed to implement a floating-point butterfly using conventional floating-point adders and multipliers. The numerical result of the fused butterfly unit is more accurate because fewer rounding operations are needed.
AB - This paper extends the consideration of fused floating-point arithmetic to operations that are frequently encountered in DSP. The Fast Fourier Transform is a case in point, it uses a complex butterfly operation. For a radix-2 implementation, the butterfly consists of a complex multiply followed by the complex addition and subtraction of the same pair of data. These butterfly operations can be implemented with two fused primitives, a fused two-term inner product and a fused add subtract unit. A floating-point fused FFT Butterfly unit is presented that performs single-precision butterfly floating-point operation in a time that is only 87% the time required for a conventional floating-point butterfly. When placed and routed in a 45nm process, the fused FFT Butterfly unit occupied about 72% of the area needed to implement a floating-point butterfly using conventional floating-point adders and multipliers. The numerical result of the fused butterfly unit is more accurate because fewer rounding operations are needed.
UR - https://www.scopus.com/pages/publications/70349662048
U2 - 10.1109/ACSSC.2008.5074512
DO - 10.1109/ACSSC.2008.5074512
M3 - Conference contribution
AN - SCOPUS:70349662048
SN - 9781424429417
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 767
EP - 771
BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Y2 - 26 October 2008 through 29 October 2008
ER -