Based on recent technological developments, high-performance floating-point signal processing can, for the very first time, be easily achieved using FPGAs. To date, virtually all FPGA-based signal ...

[Editor's note: For an intro to fixed-point math, see Fixed-Point DSP and Algorithm Implementation. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a surprisingly ...

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 applicability ...

There is a natural preference to use floating-point implementations in custom embedded applications because they offer a much higher dynamic range and as a byproduct bypass the design hassle of ...

Wong: EEMBC has been around for more than 16 years, why the recent need for floating-point benchmarks? Levy: While floating-point units in processors have been in use for decades, in recent times ...

Floating point units (fpu) can increase the range and precision of mathematical calculations or enable greater throughput in less time, making it easier to meet real time requirements. Or, by enabling ...

Here we provide rational for using Centar’s floating-point IP core for the new Altera Arria 10 and Stratix 10 FPGA platforms. After a short contextual discussion section, a comparison of various FFT ...

As defined by the IEEE 754 standard, floating-point values are represented in three fields: a significand or mantissa, a sign bit for the significand and an exponent field. The exponent is a biased ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...