Compared to software emulation, FPUs can speed up floating-point math operations by a factor of 20 to 100 (depending on type of operation) but the availability of embedded processors with on-chip FPUs ...

Because so many microcontrollers now include a floating-point unit (FPU) that performs math operations, engineers can tackle a wider range of applications that rely on precise values for control ...

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 ...

Most of the algorithms implemented in FPGAs used to be fixed-point. Floating-point operations are useful for computations involving large dynamic range, but they require significantly more ...

Floating-point arithmetic is a cornerstone of modern computational science, providing an efficient means to approximate real numbers within a finite precision framework.

A 32-bit processor is architected such that basic arithmetic operations on 32-bit integer numbers can be completed in just a few clock cycles, and with some performance overhead a 32-bit CPU can also ...

In this video, John Gustafson from the National University of Singapore presents: Beyond Floating Point: Next Generation Computer Arithmetic. “A new data type called a “posit” is designed for direct ...

The Xilinx Floating-Point Operator core allows a range of floating-point arithmetic operations that can be performed in an FPGA. The operation is specified when the core is generated through the CORE ...

I am working on a viewshed* algorithm that does some floating point arithmetic. The algorithm sacrifices accuracy for speed and so only builds an approximate viewshed. The algorithm iteratively ...