On 07/27/2026 03:48 PM, Ross Finlayson wrote:"Arrays of all types can be declared,On 07/27/2026 03:25 PM, Mild Shock wrote:>Hi,>
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There is doubt, that you write code.
How do you write code, with your
asshole? I mean you even don't under-
>
stand a simple LIPS budget post?
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Bye
>
Ross Finlayson schrieb:On 07/27/2026 11:47 AM, Johann 'Myrkraverk' Oskarsson wrote:>On 28/07/2026 2:43 AM, Ross Finlayson wrote:>Hello, here I'll post some design notes and a panel discussion with>
some
chat-bots about making some sense of the "vector-wide scalar word"
and "character machines", on commodity hardware about ubiquitous
operations.
>
>
It's considered at least tangentially relevant to comp.lang.c and
comp.lang.c++ because for example text is ubiquitous and the targets
would be low-level, while the higher-level languages would have a
same sort of patternry, and for example that libc and cstdlib are
standard, and as with regards to POSIX and Unicode and so on.
>
Please feel free to excuse or ignore, or comment as freely.
>
Thanks for reading.
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Are you generating all of your code via LLMs? Rest assured,
the LLM generated code will have subtle and sometimes not so subtle
bugs.
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Happy bughunting!
Heh, no, I write my own code, yet, words are words and those agree.
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Perhaps take a look on comp.lang.java.programmer, for example
where is given a simple way to make "Web APIs" in "Java",
with cool elite tech like "JSON" and "HTTP".
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"APIs", I learned that word in 1994 working at "The Electronic Messaging
Association", which no longer so much exists
in its current form.
>
Most of my code is doing work in prod, and has been for
decades, long after I logged out one of my dozens of aliases,
I even wrote a few lines of code in Windows, though I
lean more toward HP and Micron than Microsoft and NVIDIA.
>
I've written frameworks in front-end and back-end,
and about system code and theory,
and around the whole damn stack.
>
"These motes excitate a mouse brain immensely".
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Anyways, about "vectorizing string functions"
and "vectorizing regular expressions"
and "vectorizing parsers", that's what Viswath & Charmaigne is about,
I'd be curious your inputs if you can ignore the trolls,
like the sock-puppet farm here. It's basically figured useful
for, for example, deep inspection of Internet messages, or incremental
parsing, when implementing the text Internet protocols.
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Then, yes, it's not so relevant to "the Foundations of Mathematics
and Physics", directly, yet it is to systems programming.
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"When compiling legacy PTX code (ISA versions prior to 3.0)
containing [...], the compiler silently disables use of the ABI."
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"Would you like to buy a bridge that's also a boat?
It's rocking all over the place."
>
The specs and stable, backward compatible definitions of modern
commodity CPUs are around, people even collect them over time, they're
even in PDFs, in case you want to read one without looking over your own
electronic shoulder.
>
Which defines the ABI, ....
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and the identifier becomes an address constant
in the space where the array is declared.
The size of the array is a constant in the program.
Array elements can be accessed using an explicitly calculated byte address,
or by indexing into the array using square-bracket notation.
The expression within square brackets is either a constant integer,
a register variable, or a simple register with constant offset expression,
where the offset is a constant expression that is either added or
subtracted from a register variable. If more complicated indexing
is desired, it must be written as an address calculation prior to use."
Sounds pretty familiar, ..., then textures in graphics cards since
triangles per second are like memory segments, ..., in case you
ever read "Graphics Gems" or "Foley and Van Dam".
"A tensor is a multi-dimensional matrix structure in the memory.
Tensor is defined by the following properties:
Dimensionality
Dimension sizes across each dimension
Individual element types
Tensor stride across each dimension
PTX supports instructions which can operate on the tensor data.
PTX Tensor instructions include:
Copying data between global and shared memories
Reducing the destination tensor data with the source.
The Tensor data can be operated on by various wmma.mma,
mma and wgmma.mma_async instructions.
PTX Tensor instructions treat the tensor data
in the global memory as a multi-dimensional
structure and treat the data in the shared memory as a linear data."
Well, if that's a, "PTX tensor", data type,
that's not all what any tensors are, those are
a kind of tensor, yet, mostly they're multi-dimensional
arrays with stride built into computing for corner and edge cases,
about stride and stribe and striqe and stripe,
so you don't have to think y * h + x,
instead just calling it "x, y, z, ..." up to a grand-total
of a five-dimension non-ragged array,
just like C's.
"Tensor" sounds cool, I guess "array" was already used.
Of course there's lots of things you can build with that,
like tensorial products and so on, and about matroids
beyond the hypercubes and rows and columns and
pillars and files and i-rows,
matrices and the determinantal analysis.
They're not exactly "tensors", though,
more of a "partial" or "restricted" account.
Wow, and 64kiB memory apiece, ....
Here there's a big interest in text and lots of it,
in a serial sort of order, without too much
attachment or lock-in, yet a stable (and closed) interface.
So, then, yes, for readers in the field interested in
vectorizing (meaning, employing the parallel resources)
of common algorithms of the computers everybody already
has and tomorrow's, also, this is for "normal forms"
and "standard guarantees".
| Date | Sujet | # | Auteur | |
| 27 Jul 26 |  Re: Viswath & Charmaigne (vector-wide scalar-word and character machines) | 2 | Mild Shock | |
| 28 Jul 26 |   Re: Viswath & Charmaigne (vector-wide scalar-word and character machines) | 1 | Ross Finlayson |
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