froonly

If the UK was still relevant in the world, the BBC would continue to fund this.

California should do something similar to what Massachusetts did & implement a state income surtax of 5% for those making over $2M/yr.

That way, there's no arguing about net worth, etc...

https://www.mass.gov/news/4-surtax-on-taxable-income-the-bas...

It's not just the AIs that steal... Thom Yorke is well known for his sticky fingers...

https://www.reddit.com/r/radiohead/comments/19266y3/does_any...

HPC folks who care about performance don't use gfortran.

It's borderline dishonest to compare rust performance unless the target compiler is something like Intel's Fortran compiler from the OneAPI suite, or the newer flang compiler.

it would be nice to be able to open papers in a new tab or window on Firefox instead of this thing hijacking the standard user interface.

is there a github for this?

Getting closer every day.

https://www.nature.com/articles/s41598-024-76900-1

If what Elmo did at twitter is anything to go by, this is just a fricking disaster of gargantuan proportions waiting to happen.

Allan Holdsworth isn't on this list. Which means whoever wrote it knows less about guitar than they think they do.

Doesn't mention Geisberg forcing Mike Payne to leave PTC and Mike joining Solidworks to head their development.

For a while you could view Netflix online and rent DVDs from them.

I got paid to do the LAPACK port, back in the mid 2000s, for a federal contractor working on satellite imaging type apps. I was still a good coder, back then... Took me about a month, as I recall. Maybe 6 weeks.

But I'm one of those old-school HPC guys who believes that libraries are mostly irrelevant, and absolutely no substitute for compilers and targeted code generation.

Julia is cool, btw. It could very well end up supplanting Fortran, once they fix the poor performance code generation issues.

Never said it would hurt NVidia, only that CUDA itself isn't as strong a barrier as people seem to think it is.

But with GPU target support in LLVM, in most cases you won't need to resort to CUDA anymore.

Back in the late 90s, there was a project at SGI, called Bali, to make all their pipelines work in IEEE 32-bit floating point (they were using Intel i860 chips) so that they could do HW rendering of scenes written in Pixar's Renderman language.

Sony copied that idea for the 1st Playstation, and then folks like NVidia & 3DLabs quickly followed suit, the idea being they would enable that functionality for games like Final Fantasy.

In the early 2000s, the HPC folks realized that you could use a GPU for physics & engineering codes, and here were are 20 yrs later.

I have 40+ yrs of HPC/AI apps/performance engineering experience & I was one of the 1st people to port LAPACK and a number of other numerical libs to CUDA. Moreover, many of those major DoE + AI sites are my customers.

You should not confuse AMD's general & long-standing indifference/incompetence wrt SW with the actual difficulty of providing a portable SW path for acceleration. As Woody Allen once said: "90% of success is showing up"

But what happened in AI, when, in a very short period of time, almost everyone moved away from writing their directly in CUDA, to writing them in frameworks like Tensorflow & PyTorch is all the evidence anyone need to show just how unsound that SW obstacle is.

Mostly true, and you'll get no argument from me on the AMD & Intel are fuckwits front. Intel does ok, but AMD in particular has completely dropped the ball on the SW front, and has been doing so for at least 25 yrs.

The point I was glibly trying to get across was that even a small effort on the part of AMD to treat the SW side as seriously as NVidia does would have yielded great benefits, and not have left them so far behind.

Also, there is a lot of work going on in the gcc & llvm toolchain to not only use OpenMP to target accelerators in computationally intensive loops but, in the case of llvm, to also target tensor instructions for more efficient code generation (https://lists.llvm.org/pipermail/llvm-dev/2021-November/1537...).

It took the AI folk less than 18 months to almost completely move away from CUDA to Tensorflow and then PyTorch... LLVM, imho, is going to do the same for Sci/Eng and general code bases in the next 2 years.

CUDA is a shallow moat whose effectiveness depends entirely on NVidia convincing people to be mortally fearful of water.

lmfao at the Meta folks not giving any credit whatsoever to the company that actually came up with and implemented the infrastructure work.

wish someone would redo these books, the way they did w. the Feynman lectures. Some of the volumes were so badly printed, as to render them almost illegible.

this is misleading.... she didn't design TM's compute/networking HW, only the systems' chassis & skins.

Which is to say she was responsible for how those machines looked, but not for how they worked... She did a stellar job in that regard, tho.

503 error

Julia was meant to be a better Fortran/C++

the twitteresque counter.social social network is run by one guy, has been operating since 2017, and afaik the bills are paid simply through crowd funding.

In that light, I'd say that whether you can avoid investment capital in favor of a 100% bootstrap model is entirely a function of your ambitions.