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| Time | User | Activity | Comment |
|---|---|---|---|
| 06:50, 12 September 2018 | Xor (talk | contribs) | Comment text edited | |
| 06:49, 12 September 2018 | Xor (talk | contribs) | New reply created | (Reply to U Math Library?) |
| 05:02, 8 August 2018 | Xor (talk | contribs) | New reply created | (Reply to U Math Library?) |
| 04:21, 8 August 2018 | Enamel 32 (talk | contribs) | New reply created | (Reply to U Math Library?) |
| 04:07, 8 August 2018 | Xor (talk | contribs) | Comment text edited | |
| 04:05, 8 August 2018 | Xor (talk | contribs) | New reply created | (Reply to U Math Library?) |
| 03:39, 8 August 2018 | Enamel 32 (talk | contribs) | New thread created |
I'm very interested in what this U library does. Do you have any reference links? I've tried googling but so far have come up short.
Can't wait to see how ScalarN fares in the rumble :)
It's written by me, and not yet open sourced ;)
And it's very simple. Just have a look at Neuromancer.FastMath. U just wrapped similar things in an elegant API ;)
just found a good math library Commons Math3
it has a much better approximation of exp than the look-up-table without memory version, and is still 2x faster than StrictMath
