threedee-simd

3d math with C and SIMD intrinsics

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9Mentions

0Explicit recommenders

45GitHub stars

REPOSITORY AT A GLANCE

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What it is

3d math with C and SIMD intrinsics

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Where it is used

No documented product use has been verified yet.

What people are saying

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This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 12:45:45 PM UTC.

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Mentions over time

HN mentions by year9 dated mentions

Observed mentions: 2012-09-14 22:00:34 UTC to 2018-06-11 08:10:34 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Comments
2012	2012-01-01 00:00:00 UTC	2013-01-01 00:00:00 UTC	1	1
2013	2013-01-01 00:00:00 UTC	2014-01-01 00:00:00 UTC	2	2
2014	2014-01-01 00:00:00 UTC	2015-01-01 00:00:00 UTC	3	3
2015	2015-01-01 00:00:00 UTC	2016-01-01 00:00:00 UTC	0	0
2016	2016-01-01 00:00:00 UTC	2017-01-01 00:00:00 UTC	2	2
2017	2017-01-01 00:00:00 UTC	2018-01-01 00:00:00 UTC	0	0
2018	2018-01-01 00:00:00 UTC	2019-01-01 00:00:00 UTC	1	1

What Hacker News says

3 sources

aktau·Nov 14, 2014

For some simpler vector stuff that's only C (and basically mostly SSE), I tend to use a personal fork of this for my toy games: https://github.com/rikusalminen/threedee-simd The simplicity is what gets to me: vcross(v1, v2) * v3 (with gcc/clangs vector extensions) Great codegen too.

In Google's MathFu: a x-platform geometry math library for C++

aktau·Apr 9, 2014

This made me think of clang/gcc's vector extensions [1], which, together with __builtin_shuffle can be used to get some real "ok" cross-platform (SSE/NEON/...) SIMD code going on. An example of this in usage is [2]. That said you're right, usually the best performance can only be obtained by using really specific instructions. But in my experience, a decent performance increase can be obtained by using the generic vector extensions. Moreover, if you can use the vector extensions for a large part of the code, that means you have to write a lot less platform-specific stuff. I.e.: you increase portability anyway, since now you only have to rewrite 5 out of 20 functions instead of 20/20. Even better, they allow one to write v3 = v1 + v2 instead of v3 = _mm_add_ps(v1,v2). The first one being clearer, more portable (will generate appropriate ad

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dps or equivalent NEON, ...) and plain nicer to read. Your pcmpeqd example is a good example of an optimizer flaw. In my opinion this is orthogonal to whether or not to expose a specific or generic API. The compiler should've use the most efficient instruction for that simple idiom, period (without you telling it to use pcmpeqd). If we continue your line of reasoning, we're back to assembly for everything. [1]: https://vec.io/posts/gcc-and-clang-vector-extensions (The vector extensions allow +,-,*,/,<,>,==,!= to be naturally used for SIMD types) [2]: https://github.com/rikusalminen/threedee-simd

In .NET JIT and SIMD are getting married

aktau·Apr 4, 2014

Btw, exDM69 has a project on github written in this style (I'm almost sure he was in fact referring to this in his earlier posts): https://github.com/rikusalminen/threedee-simd

In Don't use assembly unless you're an expert