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Groups > sci.physics.relativity > #671691
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Newsgroups | sci.math, sci.physics.relativity |
| Subject | AI accelerator extend from GPU to CPU [Zero Copying] (Was: How speed up π-WAM with vector operations) |
| Date | 2026-07-27 11:21 +0200 |
| Message-ID | <11477vd$fup5$1@solani.org> (permalink) |
| References | (3 earlier) <1145hhc$fdqk$1@solani.org> <ZDGdnbf3T4PLTPv3nZ2dnZfqnPudnZ2d@giganews.com> <11470h4$gapi$1@solani.org> <11476g4$ftjl$1@solani.org> <114776f$fu5f$1@solani.org> |
Cross-posted to 2 groups.
Hi,
The nice thing about AI accelerators, pioneered
maybe by Apple Silicon and their unified memory.
The AMD APU model can be extended so that
vector and matrix operations become uniformly
available for GPU and CPU. With unified memory
already a vector operation such as:
vec_mul_add(X, 2, 3, Y)
Only needs the X and Y address. But I havent
got my head around yet how this is all organized.
Maybe a GPU has still its own GEMM cores,
but you find Apple Silicon C++/C source code,
that taps into vector and matrix operations
by Zero Copying. The Copying is left to the DMA
of the vector or matrix operation. And moderated
by the various caches. Leading to the slogan, that
multiple floating point operations become zero cost:
Some teaching can be found here
https://www.hpc-ch.org/category/topics/course-workshop/
Bye
Mild Shock schrieb:
> Hi,
>
> One could critisize that my π-WAM doesn't
> utilize GPU to the fullest, since its GPU
> backend prototype only uses scalar operations
>
> and no vector or matrix operations. And
> modern GPUs thrive on vector and matrix
> operations. Especially matrix operations giving
>
> a boost of a factor 15x or so. There are
> many papers already showing how Prolog can be
> mapped to matrix operations. Only this research
>
> is completely ignored by Prolog systems such as
> SICStus, Ciao, SWI, ECLiPSe etc.. But lets
> illustrate what vector operations could do
>
> for π-WAM, take this compilation of the Prolog
> goal between(0,1023,X), Y is X*2+3:
>
> int X;
> int Y;
> for (X=0; X < 1024; X++) {
> Y=X*2+3;
> [...]
> }
>
> With vector operations, and vectors of size
> 32 one could do:
>
> int X1;
> int[] X = new int[32];
> int X3;
> int[] Y = new int[32];
> for (X1 = 0; X1 < 1024 / 32; X1++) {
> for (int X2 = 0; X2 < 32; X2++)
> X[X2] = X1*32+X2;
> vec_mul_add(X, 2, 3, Y);
> [..]
> }
>
> Have Fun!
>
> Bye
>
> Mild Shock schrieb:
>> Hi,
>>
>> While Huggingfaces hired GG in 2026,
>> AK was hired by Anthropic in 2026:
>>
>> Andrej Karpathy (born 23 October 1986[3])
>> is a Slovak-Canadian AI researcher, who
>> co-founded and formerly worked at OpenAI
>> In 2026 he joined Anthropic as part of
>> the pretraining team.
>> https://en.wikipedia.org/wiki/Andrej_Karpathy
>>
>> But his nanochat archivement has an
>> interesting time line:
>>
>> 168 hours , Original OpenAI GPT-2 checkpoint, 2019
>> 3 hours , d24 baseline, slightly overtrained, Jan 29 2026
>> 1 1/2 hour, autoresearch round 2, Mar 14 2026
>> The best ChatGPT that $100 can buy.
>> https://github.com/karpathy/nanochat
>>
>> But what hardware was the enabler. What is the
>> NVIDIA H100 GPU even. Well the thingy is surely not
>> a Budget Laptop, performance pretty much
>>
>> dependence on data elememt size, the H100 NVL
>> version (*), and when using tensor operations,
>> and not only scalar operations:
>>
>> 8-bit towards 3000 tera flops
>> 16-bit towards 1500 tera flops
>> 32-bit towards 900 tera flops
>>
>> Cool! I guess this experiment would tap into 60
>> tera flops, since it only uses scalar operations so far:
>>
>> 11.4 Giga Lips with a Budget Laptop
>> https://github.com/Jean-Luc-Picard-2021/gigabudget
>>
>> You could perform it by migration the web application
>> using WebGPU into a node.js standalone application
>> using the dawn library for GPU access.
>>
>> Bye
>>
>> (*)
>> https://resources.nvidia.com/en-us-hopper-architecture/nvidia-tensor-core-gpu-datasheet
>>
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> Whats this "forget" trope of glue sniffing
>>> Rossy Boy with his herpes blisters?
>>>
>>> > Bulgarians, that's some real Boris and Natasha crap,
>>> > forget Hungarians and Bulgarians.
>>>
>>> Why should I forget Bulgarians,
>>> they are never on my mind. Do you
>>> see me doing ggml stuff?
>>>
>>> I only hypothesized that it is
>>> over for Python as the machine
>>> learning language or AI inferencing
>>>
>>> locally on AI laptops language, and
>>> made the ggml case, so I already forgot
>>> about them. Which might give you a glimps,
>>>
>>> why WebGPU was used for this here:
>>>
>>> 11.4 Giga Lips with a Budget Laptop
>>> https://github.com/Jean-Luc-Picard-2021/gigabudget
>>>
>>> Is an interesting choice. Even
>>> github has some Languages statistics,
>>> giving an account what I used:
>>>
>>> HTML 67.5% JavaScript 23.1% CSS 9.4%
>>>
>>> Have Fun!
>>>
>>> Bye
>>>
>>> P.S.: The example below is not p-adics,
>>> you complete imbecil moron. Its just:
>>>
>>> 7-11 cubic Solution by Pritchard & Gries
>>> https://www.cs.cornell.edu/gries/TechReports/83-574.pdf
>>>
>>> Ross Finlayson schrieb:
>>>> On 07/26/2026 10:52 AM, Mild Shock wrote:
>>>>> Hi,
>>>>>
>>>>> You see it all boils down to find your inner peace
>>>>> by an immaculate inception of some queue datatype.
>>>>>
>>>>> KOAN/Fortran-S was an early 1990s research programming
>>>>> system for distributed-memory multiprocessors . Developed
>>>>> at ENS Lyon in the early 1990s . Often listed alongside
>>>>> other historical parallel programming efforts.
>>>>>
>>>>> The Message Passing: The research explicitly
>>>>> compared the SVM approach against message passing
>>>>> on the same hardware . The finding was that SVM
>>>>> could achieve good performance without the low-level
>>>>>
>>>>> complexity of managing explicit messages, though
>>>>> the best results often came from a hybrid approach (sic!)
>>>>> Here is an interesting baseline, from Java,
>>>>> a class ElevenSingle that only does:
>>>>>
>>>>> public static void run() {
>>>>> for (int A = 1; A < 192; A++) {
>>>>> int Y = (771-A)/3;
>>>>> for (int B = A; B < Y; B++) {
>>>>> int Z = (771-A-B)/2;
>>>>> for (int C = B; C < Z; C++) {
>>>>> int D = 711-A-B-C;
>>>>> if (A*B*C == 711000000/D &&
>>>>> 711000000 % D == 0)
>>>>> System.out.println("A="+A+", B="+B+", C="+C+", D="+D);
>>>>> }
>>>>> }
>>>>> }
>>>>> }
>>>>>
>>>>> And then compare it to ElevenMulti, doing some
>>>>> Work Balancing Scheduler Tetris Game with 8 cores:
>>>>>
>>>>> ElevenSingle
>>>>> A=120, B=125, C=150, D=316
>>>>> 6.628 ms
>>>>>
>>>>> ElevenMulti
>>>>> A=120, B=125, C=150, D=316
>>>>> 1.941 ms
>>>>>
>>>>> Not great, not terrible!
>>>>>
>>>>> Bye
>>>>
>>>> Oh, that's just "tricks of p-adic arithmetic".
>>>>
>>>> Like other sock-puppet howler trolls, when confronted
>>>> with its base incredulity, it will descend to its
>>>> lower levers of the pathos variety.
>>>>
>>>> You might be happier learning about Julia trees and
>>>> raster ops, instead of shilling yet another Ramanujan
>>>> series without saying how it's made.
>>>>
>>>> Bulgarians, that's some real Boris and Natasha crap,
>>>> forget Hungarians and Bulgarians.
>>>>
>>>>
>>>
>>
>
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Re: Micro penis brain is in constant hiatus (Was: Micro penis mother sung arias) Mild Shock <janburse@fastmail.fm> - 2026-07-24 15:36 +0200
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Re: Ignoramus or Ignorabimus: I don't care (π-WAM) (Re: Micro penis brain is in constant hiatus) Lane W <cactus_DAC@yahoo.com> - 2026-07-24 08:31 -0600
You are a moron, brainless putin payed (Was: Ignoramus or Ignorabimus: I don't care (π-WAM)) Mild Shock <janburse@fastmail.fm> - 2026-07-24 18:01 +0200
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Yeah keep reading my posts, uninspired fool (Was: You are a moron, brainless putin payed) Mild Shock <janburse@fastmail.fm> - 2026-07-24 19:45 +0200
Re: Yeah keep reading my posts, uninspired fool (Was: You are a moron, brainless putin payed) Lane W <cactus_DAC@yahoo.com> - 2026-07-24 12:11 -0600
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Andrej Karpathy original gangster of Budget Laptop (Was: miniTriton CUDA is an alternative to torch variants) Mild Shock <janburse@fastmail.fm> - 2026-07-27 09:51 +0200
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Re: Why forget Bulgarians, never on my mind (Re: The Koan of pi-WAM queues [FORTRAN-S] (Was: Not SIMD, a MIMD design for NVIDIA Volta) Ross Finlayson <ross.a.finlayson@gmail.com> - 2026-07-27 01:38 -0700
The evolution of hardware and GPT-2 training (Was: Why forget Bulgarians, never on my mind) Mild Shock <janburse@fastmail.fm> - 2026-07-27 10:56 +0200
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