Engineers targeting DSP to FPGAs have traditionally used fixed-point arithmetic, mainly because of the high cost associated with implementing floating-point arithmetic. That cost comes in the form of ...

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 resources ...

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 ...

A way to represent very large and very small numbers using the same quantity of numeric positions. Floating point also enables calculating a wide range of numbers very quickly. Although floating point ...

Native Floating-Point HDL code generation allows you to generate VHDL or Verilog for floating-point implementation in hardware without the effort of fixed-point conversion. Native Floating-Point HDL ...

In this video from the HPC Advisory Council Australia Conference, John Gustafson from the National University of Singapore presents: Beating Floating Point at its own game – Posit Arithmetic. “Dr.

In March, Nvidia introduced its GH100, the first GPU based on the new “Hopper” architecture, which is aimed at both HPC and AI workloads, and importantly for the latter, supports an eight-bit FP8 ...

Q: I’ve seen much news about 64-bit systems lately. Vendors claim 64 bits are faster than 32 bits, and it seems the fastest CPUs have 64-bit capability. Can I take advantage of 64-bit operations to ...

Although something that’s taken for granted these days, the ability to perform floating-point operations in hardware was, for the longest time, something reserved for people with big wallets. This ...