digitalsignalprocessing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent res...
详细信息
ISBN:
(纸本)9781479903566
digitalsignalprocessing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent research shows that floating-point arithmetic can be made competitive by using a reduced-precision format instead of, e. g., IEEE standard single precision, thereby avoiding the algorithm design and implementation difficulties associated with fixed-point arithmetic. This paper investigates the effects of simplified floating-point arithmetic applied to an FMA-based floating-point unit and the associated software division and square root operations. Software operations are proposed which attain near-exact precision with twice the performance of exact algorithms and resolve overflow-related errors with inexpensive exponent-manipulation special instructions.
digitalsignalprocessing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent res...
详细信息
ISBN:
(纸本)9781479903573
digitalsignalprocessing (DSP) algorithms on low-power embedded platforms are often implemented using fixed-point arithmetic due to expected power and area savings over floating-point computation. However, recent research shows that floating-point arithmetic can be made competitive by using a reduced-precision format instead of, e.g., IEEE standard single precision, thereby avoiding the algorithm design and implementation difficulties associated with fixed-point arithmetic. This paper investigates the effects of simplified floating-point arithmetic applied to an FMA-based floating-point unit and the associated software division and square root operations. Software operations are proposed which attain near-exact precision with twice the performance of exact algorithms and resolve overflow-related errors with inexpensive exponent-manipulation special instructions.
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