From Newsgroup: sci.logic
Hi,
Chris M. Thomasson schrieb:
Strive to never make a compute shader wait
on something, like an empty condition of a queue, stack.
You are such a moron. GPU elasticity was
already invented in 2008 with CUDA. I posted
this quote already:
"CUDArao TEChNOLOGY UNLOCkS ThE
POWER OF TESLA MANY-CORE PROCESSORS
The CUDA C compiler simplifies many-core
programming by enabling code development
in a high-level language and optimizing code
to run on systems without knowledge of how
many cores are in the hardware. CUDA
applications automatically take advantage of
more cores or fewer cores in a system, so
they can scale from entry-level notebook
GPUs to high end GPUs in technical workstations
and further into racks of GPUs in data centers.
This allows developers to rCLcode oncerCY and
deploy on a range of systems, as well as scale
forward in time as future GPUs deliver more
performance per watt and more cores per
processor. The benefit for software users is
the opportunity to boost computing performance
simply by adding GPUs or using their existing GPUs in new ways"
https://www.nvidia.com/docs/IO/43395/NV_DS_Tesla_S1070_US_Jun08_NV_LR_Final.pdf
Today elasticity is on logical thread aka task level,
not only on "core" level or something. Don't know
exactly what CUDA did back them, maybe only
a submit elasticity, like a time sharing system. Today
you have quite some run elasticity on modern machines,
for your logical threads. Even in budget laptops
like a Ryzen AI 7 350 /w Radeon 850M.
Bye
Mild Shock schrieb:
Hi,
Ok, following the instructions here:
npm install webgpu
https://github.com/dawn-gpu/node-webgpu
I can now run webgpu also from CLI:
node.exe dogelog.mjs
Dogelog Spieler 2.2.5, Node, JavaScript 26.4.0
(c) 1985-2026, XLOG Technologies AG, Schweiz
?- ensure_loaded(library(edge/furryhaze)).
true.
?- between(1,3,_), time(expedite((between(1,100,_),
between(1,100,_), between(1,100,_)), [size(4096)])), fail.
% Zeit 1037.994 ms, GC 0.000 ms, Lips 111 k
% Zeit 1091.131 ms, GC 0.000 ms, Lips 106 k
% Zeit 1045.274 ms, GC 0.000 ms, Lips 110 k
fail.
Same benchmark result as in the browser.
Now I can rent a bigger GPU by the hour
and do some easy CLI testing.
LoL
Bye
Mild Shock schrieb:
Hi,
Chris M. Thomasson can ask 100 more questions.
I will happily answer them. But maybe I should
make a Wiki to explain the ever same things:
But, I still don't know what you main goal is?
The goal is "Prolog inferencing"
It has textures to work with in the pipeline.
I don't need textures for "Prolog inferencing"
98 more questions to go, don't give up!
Bye
Taskfreak schrieb:
On 8/1/26 05:19, Mild Shock wrote:
Hi,
Tablets and phone are more annoying to
use with WebGPU. The usual browsers don't
have a Chrome DevTools panel integrated,
so that one could do JavaScript Debugging
directly on the device. Instead one has to
use a desktop machine, and connect the
device via UBS-C , and start a Chrome
Browser there . And then start a Chrome
DevTools panel alone, that is pair with
the device, via UBS-C cable. So this way
I already see where it crashes on the
tablets and phone:
await output.mapAsync(GPUMapMode.READ)
Unhandled Promise Rejection: OperationError
The above is the error that one can re-produce
already here with this test:
11.4 Giga Lips with a Budget Laptop
https://github.com/Jean-Luc-Picard-2021/gigabudget
Not sure what exactly happens. Maybe
a form of timeout or device lost, that the
primitive HTML / JavaScript doesn't handle
gracefully yet. Maybe redimensioning the
test, so that it consumes less time would
help. Who knows? Will see. For production
use of a GPU integration I have to anyway
provide work slicing it seems.
Bye
I know that you are Hanson and I know that you are a cocksucker.
My question is, though, do you know, do, vomit, defecate, smell,
evaporate, sweat, ooze in, ooze out, fart, see, hear, sense, taste,
and GESTATE anything other than programming?
Programming is just a tool, you know. It is nothing by itself worth
even mentioning.
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