Besides claimed efficiency improvements, posits are claimed to have advantages for implementing numerical algorithms correctly compared to IEEE floats. A big part of Gustafson's book The End of Error is devoted to that, claiming to show that a range of numerical algorithms are implemented better with posits vs IEEE floats (better meaning some mix of clearer, easier to produce stability, better error bounds, etc.). It's something of a competitor to interval arithmetic in that respect [1].

A 'softposit' implementation can at least let people experiment with writing posit algorithms to investigate the claimed algorithm-design benefits, even if it's not going to beat hardware floats in speed.

[1] The interval arithmetic people don't seem very happy with his comparisons though: http://frederic.goualard.net/publications/MR3329180.pdf

Yes, those implementation are slow compared to classical floating points. The goal, as I understand it, is to let people experiment with Posits in order to prove that they bring something to the table.

As far as I read https://posithub.org/docs/Posits4.pdf there are FPGA implementations. Also in systems where floating point arithmetic isn't supported in hardware (i.e. Arduino Uno) you rely on soft fp.

Benchmark performance analysis of accuracy and speed on AVR platforms would indeed be very interesting and an actual, possible, immediate implementation scenario...