In a recent survey conducted by AccelChip Inc. (recently acquired by Xilinx), 53% of the respondents identified floating- to fixed-point conversion as the most difficult aspect of implementing an ...
Adapteva's Epiphany Floating Point Processor Core: A Leading-Edge Lithography May Finally Open Doors
Cost- and power consumption-sensitive digital signal processing applications tend to leverage fixed point processors, for a common fundamental reason: fixed-point processor cores are substantially ...
Most AI chips and hardware accelerators that power machine learning (ML) and deep learning (DL) applications include floating-point units (FPUs). Algorithms used in neural networks today are often ...
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