Since 2010, the Debian Snapshot service functions as a "wayback machine" that allows access to old packages based on dates and version numbers. However, this service has been in need for big maintenance for quite a while. Luckily, thanks to Glasklar Teknik AB and DSA in June 2024 the service has been migrated to new hardware and is now fully up and running again: enjoy https://snapshot.debian.org/

I’m pleased to announce the availability of the latest releases of SIMD Everywhere (SIMDe), version 0.8.0 and version 0.8.2, representing another year of work by over 20 contributors since version 0.7.6.

Request for help: SIMDe has only one maintainer (@mr-c)! Please inquire about assisting in new work, code review, and more.

SIMDe is a permissively-licensed (MIT) header-only library which provides fast, portable implementations of SIMD intrinsics for platforms which aren’t natively supported by the API in question.

For example, with SIMDe you can use SSE, SSE2, SSE3, SSE4.1 and 4.2, AVX, AVX2, and many AVX-512 intrinsics on ARM, POWER, WebAssembly, or almost any platform with a C compiler. That includes, of course, x86 CPUs which don’t support the ISA extension in question (e.g., calling AVX-512F functions on a CPU which doesn’t natively support them).

If the target natively supports the SIMD extension in question there is no performance penalty for using SIMDe. Otherwise, accelerated implementations, such as NEON on ARM, AltiVec on POWER, WASM SIMD on WebAssembly, etc., are used when available to provide good performance.

SIMDe is not just about implementing Intel/AMD intrinsics, it also has implementations for 99% of the ARM NEON intrinsics and in-progress support for others.

SIMDe has already been used to port several packages to additional architectures through either upstream support or distribution packages, particularly on Debian.

What’s new in 0.8.0 / 0.8.2

• 99% complete set of implementations for all NEON intrinsics have been finished, up from 56.46% in version 0.7.6! (@yyctw @wewe5215
• Start of RISCV64 optimized implementation using the RVV1.0 vector extension! Thank you @eric900115 @howjmay @zengdage.
• SIMDe PRs are tested using Fedora Rawhide (@junaruga)

As always, we have an extensive test suite to verify our implementations.

For a complete list of changes, check out the 0.8.0 and 0.8.2 release notes.

Below are some additional highlights:

X86

There are a total of 6876 SIMD functions on x86, 2930 (43.17%) of which have been implemented in SIMDe so far. Specifically for AVX-512, of the 5160 functions currently in AVX-512, SIMDe implements 1510 (29.26%).

Note: Intel has removed the intrinsics that were unique to Intel Xeon Phi (ER, PF, 4MAPS, and 4VNNIW) from their intrinsic list. SIMDe will retain those few implementations we already had, but this changes how our completeness statistics are calculated.

Newly added function families

• AES: 5 of 6 (83.33%)

  Newly AVX512 added function families

• castph: 1 of 9 (11.11%) implemented.
• cvtus_storeu: 1 of 18 (5.56%) implemented.
• fpclass: 3 of 24 (12.50%) implemented.
• i32gather: 1 of 8 (12.50%) implemented.
• i64gather: 8 of 8 :100:
• permutex: 3 of 12 (25.00%) implemented.
• rcp14: 1 of 24 (4.17%) implemented. reduce
• reduce_max: 7 of 31 (22.58%) implemented.
• reduce_min: 7 of 31 (22.58%) implemented.
• shufflehi: 1 of 7 (14.29%) implemented.
• shufflelo: 1 of 7 (14.29%) implemented.

  Additions to existing families

• AVX512BW: 7 additional, 337 of 790 (42.66%)
• AVX512DQ: 5 additional, 112 total of 376 (29.79%)
• AVX512F: 48 additional, 1087 total of 2812 (38.66%)
• AVX512_FP16: 15 additional, 17 total of 1105 (1.54%)

  Neon

  SIMDe currently implements 6608 out of 6670 (99.07%) NEON functions; up from 56.46% in the previous release!

  Newly added families

• abal
• abal_high
• abd
• abdh
• abdl_high
• addhn_high
• aes
• bfdot
• bfdot_lane
• cadd_rot
• cale
• calt
• cmla_lane
• cmla_rot_lane
• copy_lane
• cvt_high
• cvt_n
• cvta
• cvtn
• cvtp
• cvtx
• cvtx_high
• div
• dupb_lane
• duph_lane
• eor3
• fmlal
• fms
• fms_lane
• fms_n
• ld2_dup
• ld2_lane
• ld3_dup
• ld3_lane
• ld4_dup
• maxnmv
• minnmv
• mla_lane
• mla_high_lane
• mls_lane
• mlsl_high_lane
• mmla
• mull_high_lane
• mull_high_n
• mulx
• mulx_lane
• pmaxnm
• pminnm
• qdmlal
• qdmlal_high
• qdmlal_high_lane
• qdmlal_high_n
• qdmlal_lane
• qdmlal_n
• qdmlsl
• qdmlsl_high
• qdmlsl_high_lane
• qdmlsl_high_n
• qdmlsl_lane
• qdmlsl_n
• qdmlslh
• qdmlslh_lane
• qdmulhh
• qdmulhh_lane
• qdmull_high
• qdmull_high_lane
• qdmull_high_n
• qdmull_lane
• qdmull_n
• qdmullh_lane
• qmovun_high
• qrdmlah
• qrdmlah_lane
• qrdmlahh
• qrdmlahh_lane
• qrdmlsh
• qrdmlsh_lane
• qrdmlshh
• qrdmlshh_lane
• qrdmulhh_lane
• qrshl
• qrshlh
• qrshrn_high_n
• qrshrnh_n
• qrshrun_high_n
• qrshrunh_n
• qshl_n
• qshlh_n
• qshluh_n
• qshrn_high_n
• qshrnh_n
• qshrun_high_n
• qshrunh_n
• raddhn
• raddhn_high
• rax
• recp
• rnd32x
• rnd32x
• rnd32x
• rnd64z
• rnda
• rndx
• rshrn_high_n
• rsubhn
• rsubhn
• set_lane
• sha1
• sha1h
• sha256
• sha512
• shll_high_n
• shrn_high_n
• sli_n
• sm3
• sm4
• sqrt
• st1_x2
• st1_x3
• st1_x4
• st1q_x2
• st1q_x3
• st1q_x4
• subhn_high
• sudot_lane
• usdot
• usdot_lane

Finally complete families

• cvtn
• mla_lane

Getting Involved

If you’re interested in using SIMDe but need some specific functions to be implemented first, please file an issue and we may be able to prioritize those functions.

If you’re interested in helping out please get in touch. We have a chat room on Matrix/Element if you have questions, or of course you can just dive right in on the issue tracker.

When I was 10, I came out as transgender. I was a girl and I knew it.

I was one of the lucky ones.

After four painful years, I was fortunate enough to access gender-affirming health care. First testosterone blockers. Later estrogen, the stuff my peers soaked in for years while I threw myself into software development to distract from pain.

Despite being old enough to go through the wrong puberty and suffer its permanent changes, it took four years to access the medical fix. Four years of gender therapy, hard talks with doctors, and a lot of determination.

There’s a vicious myth that kids just walk into clinics and leave with hormones. Quite the opposite.

I was lucky: my parents supported me, and by then we lived near San Francisco, where a gender clinic was willing to take me as patient.

I’m 21 now. I’ll be blunt: if not for gender-affirming care, I don’t know if I would be around. If there would be FOSS graphics drivers for Mali-T860 or the Apple M1.

If I were a few years younger, lived in the wrong part of the US, that may well be the reality, because gender-affirming care is banned for minors in conservative areas across the United States. Texas, for example, would threaten to take me from my loving parents under Greg Abbott’s directive.

Even now, I’m lucky I don’t live in the wrong place: the medication I’m prescribed is banned for adults in several American states.

I fear the 2024 election. How long until there’s a ban nationwide?

In high school, I knew this day might come. I applied to Canadian universities. Canada isn’t perfect, far from it. But stripping trans rights isn’t on the ballot yet.

Growing up, we liked visiting Florida.

Now there are travel advisories against it.

One recent Florida law threatens jail time if a trans person uses the bathroom - any bathroom - in a public space. I remember in high school, arguing back against “bathroom bills” designed to marginalize trans people. They seem tame next to the vile attacks on trans people championed by Ron DeSantis.

What’s next?

Does anybody remember the Nuremberg laws?

I was raised Jewish. Growing up, we were haunted by the spectre of the Holocaust. I knew queer Germans were in the cross-hairs alongside Jews. I didn’t know that Berlin was a queer centre before Hitler came to power.

In high school, I understood if fascists came to power in the United States, I might be first to go. Nazis had a special symbol for people like me: a pink triangle superimposed on a yellow triangle. I was 16 when I wondered if one day I would be forced to wear it.

In 2020, Donald Trump used the Nazi’s symbol for political prisoners – forced to be worn in camps – to threaten leftists in a campaign ad.

Subtle.

You don’t need to like Democrats, but I need you to understand that if you vote Republican in 2024, you vote erasure. You vote oppression. You vote fascism.

Maybe you “just have some concerns” about trans kids.

I was a trans kid, and I want you to know that DeSantis, Abbott, and Trump were my nightmares. Their policies will lead to the deaths of transgender Americans. With hundreds of GOP-sponsored anti-trans bills and laws simultaneously sweeping the United States, it’s hard to believe this isn’t by design.

It doesn’t have to be that way.

The trans experience isn’t inherently defined by suffering. Not for trans kids, not for trans adults.

When treated with respect, allowed to transition, when we can access the medication we know we need, life can be great.

Personally, I have felt virtually no gender-related discomfort in years now.

I once recoiled at my reflection. Now I look in the mirror and smile at the cute woman smiling back at me. I’m surrounded by lovely friends, and we support each other. Laugh together. Cry together. Text endless stickers of cartoon sharks together. Past the shared struggle, there is immense trans joy.

When we are made to suffer – by banning our medication, arresting us for peeing, legislating our identities out of existence on the road to establishing a theocratic state – that is a policy choice.

We’re not asking for much. We don’t want special treatment. We just want respect. Life, liberty, and the pursuit of happiness.

Right now I want legislators to get the fuck out of our doctors’ office.

I’m on the board overseeing Linux graphics. Half of us are trans. If all you care about is Linux, resist the attacks on trans people.

If you have any decency, fight back.

It’s your choice.

Selected reading:

• May Anti-Trans Legislative Risk Map

• Why It Took Decades for LGBTQ Stories to Be Included in Holocaust History

• Facebook takes down another Trump campaign ad, this time for Nazi imagery

• NAACP Issues Travel Advisory in Florida

• Texas begins investigating parents of transgender teens for child abuse, according to a lawsuit. One parent works in the department involved in the investigations

I’m pleased to announce the availability of the latest release of SIMD Everywhere (SIMDe), version 0.7.6, representing more than two years of work by over 30 developers since version 0.7.2. (I also released 0.7.4 two weeks ago, but it needed a few more fixes; thanks go to the early adopters who helped me out.)

SIMDe is a permissively-licensed (MIT) header-only library which provides fast, portable implementations of SIMD intrinsics for platforms which aren’t natively supported by the API in question.

For example, with SIMDe you can use SSE, SSE2, SSE3, SSE4.1 and 4.2, AVX, AVX2, and many AVX-512 intrinsics on ARM, POWER, WebAssembly, or almost any platform with a C compiler. That includes, of course, x86 CPUs which don’t support the ISA extension in question (e.g., calling AVX-512F functions on a CPU which doesn’t natively support them).

If the target natively supports the SIMD extension in question there is no performance penalty for using SIMDe. Otherwise, accelerated implementations, such as NEON on ARM, AltiVec on POWER, WASM SIMD on WebAssembly, etc., are used when available to provide good performance.

SIMDe has already been used to port several packages to additional architectures through either upstream support or distribution packages, particularly on Debian.

What’s new in 0.7.4 / 0.7.6

• 40 new ARM NEON families implemented
• Initial support for ARM SVE API implementation (14 families)
• Complete support for x86 F16C API
• Initial support for MIPS MSA API
• Nearly complete support for WASM SIMD128 C/C++ API
• Initial support for the E2K (Elbrus) architecture
• Initial support for LoongArch LASX/LSX and optimized implementations of some SSE intrinsics
• MSVC has many fixes, now compiled in CI using /ARCH:AVX, /ARCH:AVX2, and /ARCH:AVX512
• Minimum meson version is now 0.54

As always, we have an extensive test suite to verify our implementations.

For a complete list of changes, check out the 0.7.4 and 0.7.6 release notes.

Below are some additional highlights:

X86

There are a total of 7470 SIMD functions on x86, 2971 (39.77%) of which have been implemented in SIMDe so far. Specifically for AVX-512, of the 5270 functions currently in AVX-512, SIMDe implements 1439 (27.31%)

Completely supported functions families

• MMX
• SSE
• SSE2
• SSE3
• SSSE3
• SSE4.1
• AVX
• AVX2
• F16C
• FMA
• GFNI
• CLMUL
• XOP
• SVML

Newly added function families

• AVX512CD: 21 of 42 (50.00%)
• AVX512VPOPCNTDQ: 18 of 18 💯%!
• AVX512_4VNNIW: 6 of 6 💯%!
• AVX512_BF16: 9 of 38 (23.68%)
• AVX512_BITALG: 24 of 24 💯%!
• AVX512_FP16: 2 of 1105 (0.18%)
• AVX512_VBMI2 3 of 150 (2.00%)
• AVX512_VNNI: 36 of 36 💯%!
• AVX_VNNI: 8 of 16 (50.00%)

Additions to existing families

• AVX512F: 579 additional, 856 total of 2660 (31.80%)
• AVX512BW: 178 additional, 335 total of 828 (40.46%)
• AVX512DQ: 77 additional, 111 total of 399 (27.82%)
• AVX512_VBMI: 9 additional, 30 total of 30 💯%!
• KNCNI: 113 additional, 114 total of 595 (19.16%)
• VPCLMULQDQ: 1 additional, 2 total of 2 💯%!

Neon

SIMDe currently implements 56.46% of the ARM NEON functions (3766 out of 6670). If you don’t count 16-bit floats and poly types, it’s 75.95% (3766 / 4969).

Newly added families

• addhn
• bcax
• cage
• cmla
• cmla_rot90
• cmla_rot180
• cmla_rot270
• cvtn
• fma
• fma_lane
• fma_n
• ld2
• ld4_lane
• mla_lane
• mlal_high_n
• mlal_lane
• mls_n
• mlsl_high_n
• mlsl_lane
• mull_lane
• qdmulh_lane
• qdmulh_n
• qrdmulh_lane
• qrshrn_n
• qrshrun_n
• qshlu_n
• qshrn_n
• qshrun_n
• recpe
• recps
• rshrn_n
• rsqrte
• rsqrts
• shll_n
• shrn_n
• sqadd
• sri_n
• st2
• st2_lane
• st3_lane
• st4_lane
• subhn
• subl_high
• xar

MSA

Overall, SIMDe implementents 40 of 533 (7.50%) functions from MSA.

What is coming next

Work on SIMDe is proceeding rapidly, but there are a lot of functions to implement… x86 alone has about 8,000 SIMD functions, and we’ve implemented about 3,000 of them. We will keep adding more functions and improving the implementations we already have.

If you’re interested in using SIMDe but need some specific functions to be implemented first, please file an issue and we may be able to prioritize those functions.

Getting Involved

If you’re interested in helping out please get in touch. We have a chat room on Matrix/Element which is fairly active if you have questions, or of course you can just dive right in on the issue tracker.

Standardizing computational reuse and portability with the Common Workflow Language.