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 ...
Recently I've become involved in multiple projects where inherent limitations in floating point numbers are leading to problems (for example, carry out a few hundred matrix multiplications and the ...
Floating-point arithmetic is a cornerstone of modern computational science, providing an efficient means to approximate real numbers within a finite precision framework. Its ubiquity across scientific ...
Today a company called Bounded Floating Point announced a “breakthrough patent in processor design, which allows representation of real numbers accurate to the last digit for the first time in ...
I recently received an email announcement from Texas Instruments that linked to an archived discussion of floating-point and fixed-point math with John Thorn of Texas Instruments, David Anderson of ...
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 ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback