Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]

Groups > sci.math > #646805 > unrolled thread

APU-style chips load enormous AI models (Re: Creating a "European CMOS 2.0 Army")

Back to article view | Back to sci.math

This discussion starts older than the indexed window; earlier articles aren't shown. The article labeled Started by below is the oldest one visible, not the original post.

Contents

  APU-style chips load enormous AI models (Re: Creating a "European CMOS 2.0 Army") Mild Shock <janburse@fastmail.fm> - 2026-07-16 17:19 +0200
    Donate a VT100 to vilage idiot? [Black Dildo AI Simulation] (Was: APU-style chips load enormous AI models) Mild Shock <janburse@fastmail.fm> - 2026-07-16 23:17 +0200

#646805 — APU-style chips load enormous AI models (Re: Creating a "European CMOS 2.0 Army")

Hi,

Its an error to think iGPU and APU are
only an AMD thing. Even though Intel
and Apple avoid AMD's trademarked "APU"
acronym, the core engineering philosophy

is identical: putting specialized, non-CPU
computing accelerators onto the same piece
of silicon so they can share a single,
massive pool of ultra-fast system memory
without data transfer bottlenecks.

Interestingly, this architecture has become
incredibly popular for local AI workloads,
as the unified memory pool allows these modern,
APU-style chips to load enormous AI models

that would normally require highly expensive,
specialized enterprise graphics hardware.

The Evolution of PC Architecture to
Support Local AI Workloads
https://daily.dev/posts/the-evolution-of-pc-architecture-to-support-local-ai-workloads-bys2nzlg9

Companies like AMD, Intel, and Qualcomm
are deeply invested in this race to redefine
computer capabilities, aiming to unlock
powerful on-device AI performance.

This change marks a departure from the
decades-old architecture designed around
separate processing units with individual
memory allocations, setting a new standard
in personal computing.

Bye

Mild Shock schrieb:
> Hi,
> 
> For marketing purposes people
> typically look at the race towards
> 2nm, and we find:
> 
> A month ago, Apple lost its exclusivity
> on 3 nm smartphone processors with
> MediaTek’s Dimensity 9400 chip, integrated
> in the Vivo X200 Pro smartphone. Qualcomm
> is also in the race with its recently
> unveiled Snapdragon 8 Elite and set to
> power the Xiaomi 15 Pro in 2025. However,
> Apple should regain its position as innovation
> leader in 2026 with the release of the
> iPhone 18, which should feature the A20
> chip built on TSMC’s 2 nm process."
> 
> But there is a vertical vias revolution
> going on as well, some SOCs typically
> being at 18 layers now:
> 
> Zooming Into a CPU (It's Incredible)
> https://www.youtube.com/watch?v=Bez-2cvYja0
> 
> imec has coined the term CMOS 2.0:
> 
> LEUVEN (Belgium), MARCH 12th, 2026 — Imec,
> a world-leading research and innovation hub
> in advanced semiconductor technologies, has
> launched a first-of-its-kind consortium with
> 26 European university groups that will jointly
> work on the technology roadmap beyond
> CMOS scaling (CMOS 2.0).
> https://www.imec-int.com/en/press/imec-launches-university-consortium-around-next-generation-chips 
> 
> 
> So we might see more mobile grade GPUs.
> 
> Bye

[toc] | [next] | [standalone]

#646810 — Donate a VT100 to vilage idiot? [Black Dildo AI Simulation] (Was: APU-style chips load enormous AI models)

Hi,

This is urgent. The poor guy is stuck with
a VT200. Might somebody donate an old VT100
to the poor guy?

He wants to do some vintage AI experiment,
with the Rainbow Library from 1982. Basically
a simulation how a big black dick dildo

enters his fat greasy ass. So that he can
feel the 3 KB RAM of a VT100. The 16 KB RAM
of his VT200 are too big for him.

Bye

Bobauk Modenov schrieb:
 > Mild Shock wrote:
 >
 >> an integrated GPU (iGPU) used as an APU relies
 >> entirely on shared system RAM. Because the processor
 >> and graphics chip live on the same silicon die,
 >> they do not have their own separate video memory
 >
 > idiot, yet another thing you dont undrestand, only
 > max half of the entire ram can be given to the gpu.
 > Most of the laptops gives even less, say max
 > 1 GB of the "shared" ram to the gpu. Idiot.

[toc] | [prev] | [standalone]

Back to top | Article view | sci.math

csiph-web