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I nowhere said something about AI (Re: I nowhere talked about 10GB/s)

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Hi Dumbwit,

Nobody is interested in discussing AI,
I am discussing prolog on a AI laptop.

Who cares that they use the AI marketing,
when they have splendid GPUs?

Only morons like you!

Bye

Wilfred Durmanov schrieb:
 > yet another obsolete it-supporter, without
 > proper education, doesnt know what AI stands
 > there for. Maybe you should look round to
 > have your face properly rearranged

Mild Shock schrieb:
> Hi Dumbwit,
> 
> You are a real moron right.
> 
> 11.4 Giga Lips with a Budget Laptop
> https://github.com/Jean-Luc-Picard-2021/gigabudget
> 
> What does LIPS mean. Look it up!
> Nothing to do with bytes (B).
> 
> Bye
> 
> Hint: The speed of a Prolog implementation is
> sometimes quoted in LIPS - logical inferences
> per second.
> 
> See also:
> 
> Prolog basics CSc 372, Fall 2006 Prolog, Slide 154
> W. H. Mitchell (whm@msweng.com)
> https://www2.cs.arizona.edu/classes/cs372/fall06/prolog.sli.pdf
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Insist on what? Your stupidity? I only
>> see 404 Brain not Found in your case.
>> Who cares about 10GB/s, the facts are here:
>>
>> 1 Shader      4096 Shaders
>> 542.0 ms      1141.0 ms
>>
>> Means with 4096 shaders and the problem at
>> hand, we still didn't reach the GPU
>> Knee in the case of a Ryzen AI 7 350
>>
>> w/ Radeon 860M. If you take another
>> hardware, you might see another GPU
>> saturation in the function
>>
>> f(N) = time used for N shaders.
>>
>> Bye
>>
>> P.S.: So whats YOUR hardware and GPU
>> saturation? Its all open source:
>>
>> Here is the software:
>>
>> 11.4 Giga Lips with a Budget Laptop
>> https://github.com/Jean-Luc-Picard-2021/gigabudget
>>
>> Here are the screenshots (of the timings):
>>
>> 11.4 Giga Lips with a Budget Laptop
>> https://medium.com/2989/899b0d5c027b
>>
>>  > i must insist, memory arrays on AI gpu cards
>>  > are not for graphics, idiot.
>>  >
>>  > the proof? amazing a prolog guy dont even know what is going on in
>>  > background, here the speed for embedded gpu/cpu are for instructions
>>  > timing, not AI, hence say 10GB/s, which is nothing for running llm AI.
>>
>> Mild Shock schrieb:
>>> Hey Dumbwit,
>>>
>>> We are still waiting for result. You only
>>> post gibberish:
>>>
>>> /* Gibberish I */
>>>  > idiot, embedding the graphic card gpu into
>>>  > the cpu, you already have there
>>>  > the bottleneck, low speeds in ai, disregard the ram size allocated 
>>> to the graphic card.
>>>
>>> Could you show us the bottleneck, is it
>>> in the same room as us. Whats your proof?
>>> During my testing the CPU just waits:
>>>
>>>          await outputBuffer.mapAsync(GPUMapMode.READ);
>>> https://github.com/Jean-Luc-Picard-2021/gigabudget/blob/main/course/example63/package.html#L181C1-L181C54 
>>>
>>>
>>> Whats your point ultra moron?
>>>
>>> /* Gibberish II */
>>>  > this imbecile doesnt know what ai and llm is, nor using it in 
>>> coding, programming etc, an idiot. He is doing graphics, what a fool. 
>>> AI graphic cards are not for graphics, cretin. What a fool.
>>>
>>> Could you show us where I use graphics?
>>> The screenshots? The screenshots are only
>>> timings shown. Like here:
>>>
>>>          document.getElementById("result").innerText = 
>>> i32s[0].toString() + " /* "+Math.round(performance.now() - start)+" 
>>> ms */";
>>> https://github.com/Jean-Luc-Picard-2021/gigabudget/blob/main/course/example63/package.html#L184C1-L185C67 
>>>
>>>
>>> Whats your point ultra moron?
>>>
>>> It seems you are highly confused Dumbwit!
>>> Go see a doctor as fast as you can.
>>>
>>> Bye
>>>
>>> Mild Shock schrieb:
>>>> Hey Dumbwit,
>>>>
>>>> We are waiting : 1 Month, 3 Months,
>>>> 12 Months ... Mostlikely the idiot even
>>>> doesn't own a RTX 5070. And if he owns
>>>>
>>>> a RTX 5070 he might struggle with setting
>>>> up HTTPS, so that the browser gives you
>>>> a WebGPU adapter.
>>>>
>>>> Well the good news is, you don't need
>>>> a browser. You could also run it with
>>>> node.js. Just use node.js dawn.
>>>>
>>>> See also
>>>>
>>>> Llamas on the Web: Memory-Efficient,
>>>> Performance-Portable, and Multi-Precision
>>>> LLM Inference with WebGPU
>>>> Reese Levine et al. -- 20 May 2026
>>>> Figure 2: Breakdown of the LlamaWeb llama.cpp WebGPU
>>>> backend and its different paths for executing on GPUs.
>>>> https://arxiv.org/abs/2605.20706
>>>>
>>>> But I didn't prepare some node.js code
>>>> on my GitHub. I also dont use some WASM (*)
>>>> helpers, its just pure HTML that taps
>>>>
>>>> into WebGPU via JavaScript inside a HTML page.
>>>>
>>>> Bye
>>>>
>>>> (*) Compute Toys seems to use WASM
>>>> to support Slang besides WGSL.
>>>>
>>>> Mild Shock schrieb:
>>>>> Hey Dumbwit,
>>>>>
>>>>> just run it on your RTX 5070 trash. I am
>>>>> software developer, not a hardware
>>>>> develper. I don't care what hardware
>>>>>
>>>>> people use. Here is the software:
>>>>>
>>>>> 11.4 Giga Lips with a Budget Laptop
>>>>> https://github.com/Jean-Luc-Picard-2021/gigabudget
>>>>>
>>>>> Here are the screenshots:
>>>>>
>>>>> 11.4 Giga Lips with a Budget Laptop
>>>>> https://medium.com/2989/899b0d5c027b
>>>>>
>>>>> You see in the screenshots with a
>>>>> Ryzen AI 7 350 w/ Radeon 860M that the
>>>>> results are:
>>>>>
>>>>> 1 Shader      4096 Shaders
>>>>> 542.0 ms      1141.0 ms
>>>>>
>>>>> What does your RTX 5070 trash deliver?
>>>>> Just redo the experiment on your hardware.
>>>>> If the figures are better, well good for
>>>>>
>>>>> you. If the figures are worse, well I wouldn't
>>>>> care less. You are just wasting everbodies
>>>>> bandwidth with your idiotic posts, and being
>>>>>
>>>>> lazy, instead of replicating the experiment
>>>>> on your RTX 5070 trash.
>>>>>
>>>>> Bye
>>>>>
>>>>> Olin Bagramov schrieb:
>>>>>  > Mild Shock wrote:
>>>>>  >
>>>>>  >> a wider von Neuann Neck. You can try yourself, in case you find 
>>>>> an AI
>>>>>  >> Laptop with similary specs as the Radeon 860M.
>>>>>  >
>>>>>  > idiot, that's nothing in llm, you are wasting your time
>>>>>  >
>>>>>  > compare with this, if you want proper llm
>>>>>  >
>>>>>  > HBM3e: The current flagship memory for the H200 and B200 series, 
>>>>> offering
>>>>>  > the highest bandwidth (~8 TB/s) required for trillion-parameter 
>>>>> models.
>>>>>  >
>>>>>
>>>>>  >> Hi,
>>>>>  >>
>>>>>  >> You are a fucking moron, arent you?
>>>>>  >>
>>>>>  >> Most of the stuff in my pi-WAM happens inside the L1 and L2 
>>>>> caches of
>>>>>  >> the GPU.
>>>>>  >> Which is faster than normal RAM and has
>>>>>  >>
>>>>>  >> a wider von Neuann Neck. You can try yourself, in case you find 
>>>>> an AI
>>>>>  >> Laptop with similary specs as the Radeon 860M.
>>>>>  >>
>>>>>  >> The example is open source:
>>>>>  >>
>>>>>  >> 11.4 Giga Lips with a Budget Laptop
>>>>>  >> https://github.com/Jean-Luc-Picard-2021/gigabudget
>>>>>  >
>>>>>  > L1 and L2 are small in size and slow, then the 6 stages 
>>>>> pipelining destroys the neural AI/llm algorithm; compare that with 
>>>>> 4,000 GB/s arrays gddr7 for a graphic card, then talk. You are not 
>>>>> good at numbers, are you
>>>>
>>>
>>
> 

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      Dumbwit, just run it on your RTX 5070 trash (Re: he Wider von Neumann Neck) Mild Shock <janburse@fastmail.fm> - 2026-07-10 15:47 +0200
        We are waiting Dumbwit: 1 Month, 3 Months, .. [node.js dawn] (Re: Dumbwit, just run it on your RTX 5070 trash) Mild Shock <janburse@fastmail.fm> - 2026-07-10 16:29 +0200
          We are still waiting for results! [Confused Dumbwit] (Re: We are waiting Dumbwit: 1 Month, 3 Months, .. [node.js dawn]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 22:47 +0200
            404 Brain not Found [GPU saturation] (Re: We are still waiting for results! [Confused Dumbwit]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:42 +0200
              I nowhere talked about 10GB/s (Re: 404 Brain not Found [GPU saturation]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:43 +0200
                I nowhere said something about AI (Re: I nowhere talked about 10GB/s) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:51 +0200
                Re: I nowhere said something about AI (Re: I nowhere talked about 10GB/s) Mild Shock <janburse@fastmail.fm> - 2026-07-11 00:09 +0200
                micro penis got hurt by "budget" (Re: SWI makes only MLips not GLips) Mild Shock <janburse@fastmail.fm> - 2026-07-12 19:20 +0200

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