Because fixed-point DSPs are consumed in large volumes, their price per chip is a fraction of the price of a floating-point DSP. As a result, the only developers who can reasonably justify using a ...

Floating-point operations are useful for computations involving large dynamic range, but they require significantly more resources than integer operations.

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

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 ...

With floating-point arithmetic being at the core of many modern AI chips, and dozens of start-ups involved in the development of AI accelerators, it is crucial to provide easy-to-use formal ...

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 ...

The background: In the world of high-performance computing, the number of floating-point arithmetic operations performed per second with double (64-bit) precision is a benchmark for the ...

Different floating-point formats allow machine-learning systems to operate more efficiently and use less space.