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 ...
Hardware for integer or fixed-point arithmetic is relatively simple to design, at least at the register-transfer level. If the range of values and precision that can be represented with these formats ...
The uM-FPU64 floating point coprocessor chip provides support for IEEE 754-compatible, 64-bit floating point and integer calculations, expanded digital I/O, and analog input capabilities as well as ...
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