Stephen Fuld <sfuld@alumni.cmu.edu.invalid> schrieb:
> On 8/8/2023 3:08 PM, MitchAlsup wrote:
>> On Tuesday, August 8, 2023 at 4:53:39 PM UTC-5, Quadibloc wrote:
>>> On Tuesday, August 8, 2023 at 3:28:42 PM UTC-6, Thomas Koenig wrote:
>>>> MitchAlsup <Mitch...@aol.com> schrieb:
>>>
>>>>> Still, overall, posit gives you more of what you want--precision
>>>>> when you don't need exponent bits, and lack of precision loss
>>>>> when you do.
>>>
>>>> I'm thoroughly unconvinced on posits.
>>>>
>>>> Losing precision when the scale is off seems like a bad idea to me,
>>>> especially if there is no indication of lost intermediate precision.
>> <
>> There are (now) many numerical algorithms which have been tested in
>> posit form and found to have significantly better accuracy with posits
>> instead of IEEE 754--so much so that some of them can decrease the
>> size of their average data (63->32 or 32->16) and still give meaningful
>> results--mostly better than IEEE of 2× the size
>> <
>> However, I too remain unconvinced--because the failed results are not
>> equally marketed..
>
> Agreed. Though I did find this
>
> https://arxiv.org/pdf/2109.08225.pdf
>
> Which gives at least some real world examples where Posits are worse.

Interesting to read that.

They compared 8- and 16-bit posits agains 32-bit IEEE. Lacking,
IMHO, is the comparison against 16-bit IEEE, which might also have
been interesting.