The graph below shows the total number of publications each year in Floating-Point Arithmetic and Algorithms. References [1] A practical streaming approximate matrix multiplication algorithm .

Migrating signal-processing algorithms from floating- to fixed-point is often necessary to meet various design constraints, including real-time performance, cost and power dissipation. The migration ...

[Editor's note: For an intro to floating-point math, see Tutorial: Floating-point arithmetic on FPGAs. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a ...

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 ...

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 ...

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 ...

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 ...

Floating-point arithmetic is a cornerstone of numerical computation, enabling the approximate representation of real numbers in a format that balances range and precision. Its widespread ...