10 ms·

> I can't think of any other company that has managed to benefit so much from a product designed for one thing, that turned out to be the solution to other thin

> I can't think of any other company that has managed to benefit so much from a product designed for one thing, that turned out to be the solution to other things as well. CUDA was first released in 2007: * https://en.wikipedia.org/wiki/CUDA https://en.wikipedia.org/wiki/CUDA * https://developer.download.nvidia.com/compute/cuda/1.0/NVIDIA_CUDA_Programming_Guide_1.0.pdf https://developer.download.nvidia.com/compute/cuda/1.0/NVIDI... Two years before the Bitcoin paper (2009): * https://en.wikipedia.org/wiki/Bitcoin https://en.wikipedia.org/wiki/Bitcoin They had a presentation called "The Era of the Personal Supercomputing" at SIGGRAPH 2007: * https://dl.acm.org/doi/10.1145/1281500.1281647 https://dl.acm.org/doi/10.1145/1281500.1281647 * https://www.nvidia.com/content/events/siggraph_2007/supercomputing.html https://www.nvidia.com/content/events/siggraph_2007/supercom... Ian Buck (co-?)creator of CUDA speaking in 2008: > Ian Buck talks about his background developing Brook for GPUs at Stanford university and what paths were taken for developing a C platform for GPUs. * https://www.youtube.com/watch?v=Cmh1EHXjJsk https://www.youtube.com/watch?v=Cmh1EHXjJsk > In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs. Ian Buck later joined NVIDIA and led the launch of CUDA in 2006, the world's first solution for general-computing on GPUs. * https://developer.nvidia.com/cuda-zone https://developer.nvidia.com/cuda-zone * http://graphics.stanford.edu/~ianbuck/ http://graphics.stanford.edu/~ianbuck/ Nvidia purposefully went after parallel computing. Specific applications (cryptocurrency, ML/AI) appeared later.

EduardoBautista 3y ago
A strong argument can be made that Nvidia helped these technologies gain traction.
- PaulHoule 3y ago
  In the early 2000s it was a common theme in the CS literature that the Von Newman architecture was about to run out of steam and some kind of parallel processor was going to become mainstream, out of all that work the GPGPU became the most famous. If NVIDIA hadn’t done it, someone else would have.
  - freedomben 3y ago
    Heh, I remember that too. Von Neumann architectures being legacy was all the rage, and many students were excited to be able to build the next thing.
  - joe_the_user 3y ago
    Indeed, The thing is, Nvidia has "done it" and still no one else is "doing it". As the gp points out, Nvidia launched CUDA a while and this made Nvidia's products general purpose parallel processors. They have succeeded as that and yet still no one is selling chips that either have an equivalent interface or (better) are drop-in Cuda compatible (since we know interfaces and programming language copyrightable). The situation seems a bit like early PC days when companies sold (roughly) PC compatible computers were appropriately shoved aside by drop-in compatible clones/white-boxes. A company that makes a thing "kinda like" the leader but with it's own sauce is just trying to carve a piece of an existing market. The company that makes something exactly compatible with the leader has an incentive to go further. I hate to say "embrace and extend" but there you have it.
- josu 3y ago
  Not crypto. Bitcoin had a very short GPU phase that spanned for a few months, before moving to FPGAs and finally to ASICs. Ethereum made a concerted effort to sabotage ASIC mining, and remain GPU minable. Such is the case for all other GPU minable coins. So no, I don't think crypto needed GPUs. Related to that, I feel like AI should start moving to FGPAs/ASICs soon.
PaulHoule 3y ago
My own personal history has to do with it, because when I was doing my PhD work they defunded our supercomputing center. Parallel computing went from being “the future” to a boring backwater dominated by the military industrial complex and a handful of ‘boondoggle’ projects like figuring out how proteins fold in water which turned out to be a waste of time because we found out proteins don’t “fold” but instead they get folded. I diagonalized a 65 spin cluster on an IBM AIX machine if I used a supercomputer I could have diagonalized a spin 90 maybe and it wouldn’t have made any difference in the results. Turned out having a powerful computer on your desktop was revolutionary and having to fill out paperwork to run your job was just… a tired old throwback. I got a lot more excited about commercial “big data” developments in the 2000s as these completely escaped the gravity of the national labs and the handful of problems they do over and over again.

EduardoBautista 3y ago

A strong argument can be made that Nvidia helped these technologies gain traction.

PaulHoule 3y ago
In the early 2000s it was a common theme in the CS literature that the Von Newman architecture was about to run out of steam and some kind of parallel processor was going to become mainstream, out of all that work the GPGPU became the most famous. If NVIDIA hadn’t done it, someone else would have.
- freedomben 3y ago
  Heh, I remember that too. Von Neumann architectures being legacy was all the rage, and many students were excited to be able to build the next thing.
- joe_the_user 3y ago
  Indeed, The thing is, Nvidia has "done it" and still no one else is "doing it". As the gp points out, Nvidia launched CUDA a while and this made Nvidia's products general purpose parallel processors. They have succeeded as that and yet still no one is selling chips that either have an equivalent interface or (better) are drop-in Cuda compatible (since we know interfaces and programming language copyrightable). The situation seems a bit like early PC days when companies sold (roughly) PC compatible computers were appropriately shoved aside by drop-in compatible clones/white-boxes. A company that makes a thing "kinda like" the leader but with it's own sauce is just trying to carve a piece of an existing market. The company that makes something exactly compatible with the leader has an incentive to go further. I hate to say "embrace and extend" but there you have it.
josu 3y ago
Not crypto. Bitcoin had a very short GPU phase that spanned for a few months, before moving to FPGAs and finally to ASICs. Ethereum made a concerted effort to sabotage ASIC mining, and remain GPU minable. Such is the case for all other GPU minable coins. So no, I don't think crypto needed GPUs. Related to that, I feel like AI should start moving to FGPAs/ASICs soon.

PaulHoule 3y ago

My own personal history has to do with it, because when I was doing my PhD work they defunded our supercomputing center. Parallel computing went from being “the future” to a boring backwater dominated by the military industrial complex and a handful of ‘boondoggle’ projects like figuring out how proteins fold in water which turned out to be a waste of time because we found out proteins don’t “fold” but instead they get folded. I diagonalized a 65 spin cluster on an IBM AIX machine if I used a supercomputer I could have diagonalized a spin 90 maybe and it wouldn’t have made any difference in the results. Turned out having a powerful computer on your desktop was revolutionary and having to fill out paperwork to run your job was just… a tired old throwback. I got a lot more excited about commercial “big data” developments in the 2000s as these completely escaped the gravity of the national labs and the handful of problems they do over and over again.