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microsoft
DirectXMath
C++2018–2025
microsoft / DirectXMath

DirectXMath

DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps

Creative & MediaSystems & InfrastructureGames & EmulationScience & EngineeringMobile & DesktopLibraries & SDKs
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4Distinct people
15Mentions
0Explicit recommenders
1.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 3:30:57 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year15 dated mentions

Observed mentions: 2018-03-06 21:50:20 UTC to 2025-01-27 17:18:10 UTC.

012342018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025

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

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC202
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC404
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC303
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC303
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202

What Hacker News says

4 sources
dvt·Jul 19, 2020
> Despite both are within specs, the results are numerically different. True, but it's quite common that floating point ops throwaway bits (i.e. beyond the epsilon) will be numerically different between vendors. > Modern DirectXMath doesn‘t use these approximated instruction for inverting matrices, it’s open source, there: https://github.com/microsoft/DirectXMath/blob/83634c742a85d1.... Good find, neither does Wine, actually: https://doxygen.reactos.org/dc/dd8/d3dx9math_8h.html#a3870c6... Would be interesting to see if this bug also happens on Linux.
In Fixing Mass Effect black blobs on modern AMD CPUs
corysama·Apr 10, 2020
The megahertz-scaling "Free Lunch" was declared dead 15 years ago [http://www.gotw.ca/publications/concurrency-ddj.htm] and it's been only getting deader. People are finally, grudgingly accepting that they must go parallel unless we want to see software performance stagnate permanently. For most people here, the issue has been obvious since before they learned to program. But, still they are putting off learning how to deal with it. The first, obvious answer to that is threading. But, in my experience, SIMD is a bigger bang for the buck for two reasons: 1) No synchronization problems. 2) Better cache utilization. It's not just that SIMD forces you to work in large, contiguous blocks. Fun fact: When you aren't using SIMD you are only using a fraction of your L1 cache bandwidth! A big challenge is that SIMD intrinsic-function APIs a
Read the rest
re weird. They have inscrutable function names and sometimes difficult semantics. What helped me greatly was going through the effort of writing #define wrappers for myself that just gave each function in SSE1-3 names that made sense to me. I don't expect many people to put in that effort. And, unfortunately, I don't have go-to recommendations for pre-existing libraries. Best I can do is: https://github.com/VcDevel/Vc is working on being standardized into C++. It's great for processing medium-to-large arrays. https://ispc.github.io/ is great for writing large, complicated SIMD features. https://github.com/microsoft/DirectXMath is not actually tied to DirectX. It's has a huge library of small-vector linear algebra (3D graphics math) function. It used to be pretty tied to MS's compiler. But, I believe they've been cleaning it up to be cross compiler lately.
In SIMD instructions

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