I feel like saying they got "lucky" after trying and failing in multiple other endeavors requires a special definition of luck. If someone rolls a 6 sided die six times and they roll a six once did they get lucky?
You'll find out when you read TFA!
Stop downplaying markets because of X. The market-share of the PC gaming market is higher than most modern countries of the world.
TFA says that Nvidia started aggressively seeding CUDA and GPUs for research in the early 2010s. It was much earlier than that: it started pretty much immediately after CUDA was introduced late 2006. And every new generation there were hardware features added to make GPU programming and porting of applications less painful. The first Nvision conference, precursor of GTC, was in 2008. That’s how you make your own luck.
I’ll never forget when, sometime around 2012?, he answered the question: “aren’t you afraid Intel?”
His answer: “Not at all. Intel should be afraid of us. We will be bigger than them.” There was not a trace of doubt.
(Bit of a tangent, but that project was very influential in getting me interested in computer science because, wow, how cool is it that we can use GPUs to do insane parallel computing. So I guess, very very indirectly, Nvidia had a part in me being a software engineer today.)
https://developer.nvidia.com/gpugems/gpugems2/part-iv-genera...
I don’t remember it getting much more traction after that: as soon as CUDA was released, end of 2006, it was game over.
https://www.nvidia.com/en-us/shield/support/shield-tv/introd... https://www.nvidia.com/en-us/geforce-now/
I use them everywhere and have a big pile of chromecasts, satellite boxes, remote controls and Apple tvs now ready for eBay!
Given all the times that HN readers have derided grandiose executive pronouncements preceding flops, more people should recognize the above for what it is: not profundity but just puffery that happened to pan out. Not that skill and effort weren't involved in making it pan out but that any of a zillion things could have gone wrong to make that statement false and part of any manager's job is to project confidence and instill motivation despite knowing that.
This time it worked out. Can’t give it a survivorship bias. I don’t personally mind CEOs being encouraging, but at least understand that they don’t really ever know.
Credit for going after a vision, but every CEO has a vision and acts like it will inevitably happen.
Everybody's known that Moore's law was on its way out, for speed increases at least, since the mid 2000s - the seminal article was by Herb Sutter [1]. So hardware needed to get more parallel. But multicore is a distinctly different paradigm to CUDA, which is closer to SIMD but on a completely different order of magnitude. So Intel was never going to get to where the puck was skating.
The statement: "Not at all. Intel should be afraid of us. We will be bigger than them." is still true.
How is it true? Gaming rigs. No matter what processor people chose, people overwhelmingly choose Nvidia graphics cards.
If Intel was inside 50% of the market's rigs, Nvidia is in 70+% of those same rigs.
The statement wasn't puffery. The statement was made with naked, and overwhelming, confidence.
I was at a niche graphics app startup circa 2000-2005 and even then NVidia invested enough to be helpful with info and new hardware, certainly better than other GPU companies. Post 2010 I was at a F500, industry leading tech company and an NVidia Biz Dev person came to meet with us every quarter usually bearing info and sometimes access to new hardware.
It's also worth noting that NVidia has consistently invested more than their peers in their graphics drivers. While the results aren't always perfect, NVidia usually has the best drivers in their class.
We already knew some of the possibilities when looking at Renderman, or early GPGPU attempts like the TMS34010.
Reality is Mellanox has never been a substantial networking player. Yes, in HPC, but that's a tiny market even today.
It doesn't help that Mellanox acquired Cumulus just prior to Nvidia acquiring Mellanox, and Cumulus was basically DOA. Now they are split SONiC/Cumulus with a lot of internal infighting trying to keep Cumulus relevant despite industry trends.
https://top500.org/lists/top500/2023/06/
[edit] correct the cut off link
AMD shall own OpenCL and boost it heavily and make it a central piece for its ROCm framework as the preferred backend, in my opinion.
Apple has ditched it for metal. AMD has ditched it for ROCm which is just a AMD compiler for CUDA PTX.
OneAPI is focused on C++, and it remains to be seen if Data Parallel C++ isn't also Intel's CUDA, even if based on SYCL.
SPIR so far has hardly got any adoption to the level of PTX, regarding polyglot compute.
They saw the potential of GPU compute very early on, invested in it long term and as a result eventually ended up dominating the market. The others didn't seriously commit and so they fell behind. AMD still can't seem to commit, while Intel seems to be working hard on catching up.
While I agree that Nvidia positioned themselves well, they were not looking as far forward as you suggest. As I recall it, they seemed surprised by BrookGPU, though they moved quickly to embrace the model.
And there were earlier proto examples of GPU compute that that were completely overlooked: https://web.archive.org/web/20010607021839/http://freespace.... (scroll down to "Optimising with 3D Rendering Hardware")
I don't really think Nvidia's luck is really just a luck. After all, they has the vision for CUDA, bet money on it, and succeeded. They CAN stop the effort at any point during the adventure, but they choose to continue. That's not luck, that's a vision.
BTW, the same book got picked up by some Chinese talk heads as an perfect demonstration showing the good side of capitalism, which I totally agreed. After all, if Nvidia was a Chinese company, they'll probably instead put their efforts into developing some massive-spying citizen-incriminating policewrongs-neverseening camera with funding provided by the government, thus almost guaranteed "success". I'm really glad that Nvidia is operating in a country where "making hardware so everyday people can use their computers to play games" is not something to be mocked at by it's (abusive)parents-acting government. Now, look who's paying smugglers for those A100 chips at double the price while crying? A well deserved fate on my book.
So again, "lucky success" maybe not just luck.
(BTW. I'm super concerned about all the incredible amount of power nvidia has now and in the future. They get to decide the fate of the human race, I feel. And their incentive is just to make as much money as possible, while all negative externalities including the likes of extinction is left to the society to deal with. Sigh.)
this seems like a bit of contradiction to me. they either got luck as you claim, or CUDA was good to keep things going. from my experience, CUDA was the only way to go for GPU accelerated processing. specifically, my experience was with Resolve color correction and using CUDA was the only way to go. memory is fuzzy, but the timeline on crypto was sametime-ish. because of the audience, this forum is naturally going to trend crypto vs niche video post workflows, but CUDA was definitely kicking Radeon/AMD ass in other aspects besides useless crypto.
To me the situation looks quite clear: a GPU has vastly more compute than a CPU. As time goes, we will need and use more and more compute. You just need a way (general purpose language or API) to use that GPU. For some reason, other companies in this space did not see this.
One is a framework, language extensions etc., the other is “heyy here’s an assembler for this year’s GPUs”
Everyone on the panel reacted surprised that it would be something that anyone would want to do, and most of the answers were the kind of talk to us later.
Meanwhile PGI was shipping Fortran for CUDA, this was before them being acquired by NVidia.
This pattern is pretty common in industry. Almost all the huge companies that are winners in technology are those that got on the market and kept the thing alive - that's not sufficient, but it is necessary.
Nvidia's moat is AI.
Ironically, that's what ultimately made Nvidia the winner for gpu mining: ATI gpus had been massively deployed for Bitcoin mining prior to the dominance of mining asics. When people created new altcoins they specifically designed their work functions so that they the inventors could have an advantage vs the general public, so they designed them for nvidia gpus rather than what was already deployed. This let them buy up gpus before shortages came into effect and delayed competition from the installed base.
Sure, you can trivially port whatever to whatever, but outside of startup effect mining is naturally perfectly competitive. Being 20% less efficient vs costs means bankruptcy.
> Nvidia's moat is AI.
Nvidia had a gpu computing moat before the current AI fad, due to maturity of the CUDA ecosystem. At least AI codes are generally pretty easy to port to other architectures.
The first big mining wave was 2014-2015. This was done on 5850s, and GCN 1 and 2 GPUs. This was Bitcoin, so it was computation-focused, and I think in this era it was definitively AMD dominated due to VLIW allowing very dense execution resources plus early GCN having a large amount of raw integer processing power.
The next was 2017-2018. By this era bitcoin itself had moved off to FPGAs and ASICs, so this was around Ethereum which primarily worked based on proof of memory bandwidth. AMD GPUs were falling behind Maxwell/Pascal in terms of their memory compression (although they did use it) so they were equipped with more memory bandwidth to compensate. So for a given AMD card (Polaris, Vega, etc) you got more memory bandwidth per $, but in terms of the actual compute efficiency, NVIDIA had already pushed ahead even in Ethereum. NVIDIA was usually superior per-watt and AMD just let you burn more watts. However when it came to altcoins, where it was not just raw bandwidth, NVIDIA's superior compute/GPGPU efficiency took over and there were some coins that NVIDIA was 2x or more more efficient on per-watt and also the winner in absolute watts.
(the thing to remember is that compute is the part that ASICs can do efficiently, and I always questioned whether those altcoins were really ASIC-resistant.)
This state of affairs persisted throughout the 5700 series until AMD launched the 6000 series, where they shifted to a design with smaller memory buses and more cache, which put them in the inverse situation of 2014-2015 where they were getting more out of a weaker memory subsystem than NVIDIA. And I think they did this on purpose because they wanted to "opt out" of the mining boom/bust cycle, and NVIDIA made a similar approach with Ada that has been extremely unpopular (despite AMD leading the way on this a few years before on their cards too).
Isn't it wonderfully coincidental that out of any amount NVIDIA could have put into the LHR to slow down when it detected mining, that they put in the exact amount that dropped their cards to the same relative mining performance as AMD, and moved to the same cache-based approaches in the next generation as well? That has always been my take around LHR - it's not that they didn't like mining revenue, it's that they didn't want NVIDIA cards to be disproportionately pulled off shelves like happened to AMD in the 2014 and 2017 mining booms. People remember the "AMD was $1600, NVIDIA was $2400" situation already, they didn't want that to persist and turn into actual marketshare.
Secondly, the anti-CUDA alternatives all suck, as they keep heads down on their C first approach instead of being a polyglot ecosystem.
SPIR, HIP and whatever else, lack the tooling, had a very cold embrace of C++ features, and little else, and the drivers, oh boy.
Really? What do you think high-end drones and self-driving cars are using. They invested in generic robotics software and hardware probably more than all others put together. When you go beyond Raspberry Pi it's only NVidia. Their day is coming. Another similar ecosystem will be hard to create.
What are they using?
It allows for machine vision and heavy maths to be executed very fast. There is basically nothing similar in an embedded format in the market. The remainder would be SoCs for Android phones (Samsung Exynos?).
Thsese SoCs have lots of hacky drivers and mostly support Android, which is not a very good fit for real time and high customization required for drones and self driving cars (AOSP build system, a google class piece of crap).
Those of us who were unlucky enough to buy a AMD GPU based on 'flop-count' were hurt quite badly. Nvidia's software compute-infra is simply unmatched.
You can only profit from luck if you prepare for it.
NVidia has always been the first choice for graphics work, and especially now with large complex VFX pipelines there really isn't an alternative - particularly since most of that work is done on Linux which has always had excellent support from NVidia.
then its parallel GPU got "lucky", first the bitcoin mining, then the AI. it probably did not expect and plan for this, to some extent, it got super lucky.
credit must be given to its CUDA ecosystem and the ability to better itself when chances knocked its door, it so far left all competitors in the dust, its showtime arrived, finally.