The Ledger
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Huang: NVIDIA is only accelerator maker with universal architectural compatibility
“We are the only accelerator on the planet where every single accelerator is architecturally compatible with the others. None has ever existed.”
Rosenthal: Replicating NVIDIA's 15-year CUDA stack is an enormous challenge
“This is 15 years of CUDA and the hardware underneath it and the libraries on top of it that Nvidia has built. To go recreate that and surpass it on your own is such an enormous, enormous bite to bite.”
AMD lacks Nvidia's TSMC advanced packaging capacity and CUDA developer ecosystem
“AMD doesn't have all this capacity reserved from TSMC, at least not for the 2.5 D packaging process for the high end GPUs. AMD doesn't have the developer ecosystem from CUDA.”
NVIDIA and CUDA constitute a platform on par with Apple and Microsoft
“NVIDIA is a platform, in my mind, no doubt about it. CUDA and NVIDIA and general purpose computing on GPUs is a platform, so whatever, you know, all of the stew of powers that go into making that, that go into making Apple, Microsoft, you know, and the like, G…”
Huang: NVIDIA has 250M to 300M active compatible CUDA GPUs globally
“There are literally a couple of hundred million, right? 250,000,300 million installed base of active CUDA GPUs being used in the world today, and they're all architecturally compatible.”
Huang: GeForce NOW was NVIDIA's first data center product, preceding CUDA supercomputing
“GeForce Now was NVIDIA's first data center product. And our second data center product was remote graphics, putting our GPUs in, in the world's enterprise data centers, which then led us to our third product, which combined CUDA plus our GPU, which became a su…”
NVIDIA's programmable shaders were the first massively parallel processors
“And if you just looked at the pipeline of a programmable shader, it is a processor and is highly parallel, and it is massively threaded, and it is the only processor in the world that does that.”
Nvidia has an installed base of 500 million CUDA-capable GPUs globally
“Today there are five hundred million CUDA capable GPUs for developers to target.”
Gilbert: CUDA was not a useful platform for six-plus years after 2006
“Because while CUDA development began in 2006, That was not a useful usable platform for six plus years at NVIDIA.”
Rosenthal: CUDA software cannot be deployed on non-NVIDIA chips
“You do any of this work, you cannot deploy it on anything but NVIDIA chips.”
Rosenthal: AlexNet on CUDA was the 'big bang' moment for AI
“We cannot overstate the importance of this moment, not just for NVIDIA, but for, like, computer science, for technology, for business, for the world, for us staring at the screens of our phones all day every day. This was the big bang moment for artificial int…”
Gilbert: NVIDIA's investment in CUDA was an iPhone-sized bet
“Those were big bets relative to the company's size at the time, but this bet is like an iPhone-sized bet.”
AlexNet Was Trained on Two Off-the-Shelf Nvidia GTX 580 GPUs
“They buy two NVIDIA GeForce GTX five eighties, which were NVIDIA's top of the line gaming cards at the time. The Toronto team rewrites their neural network algorithms in CUDA, NVIDIA's programming language. They train it on these two off the shelf GTX five eig…”
Huang: CUDA is used across almost all fields of scientific research
“CUDA is used for almost all fields of science. Everything from molecular dynamics to imaging, CT reconstruction to seismic processing to, you know, weather simulations, quantum chemistry, the list goes on, right?”
AlexNet was trained on two consumer Nvidia GeForce GTX 580 GPUs
“And what these guys from Toronto did is they went out probably to their local Best Buy or equivalent in Canada. They bought two GeForce GTX-Five-Eighty's, which were the top-of-the-line cards at the time, and they wrote their algorithm, their convolutional neu…”
Nvidia's CUDA platform reached four million registered developers by May 2023
“If you look at the number of CUDA developers over time, it was released in 2006, It took four years to get the first 100,000 people. Then by twenty-sixteen, 13 years in, they got to a million developers. Then just two years later, they got to two million. So 1…”
Ben Gilbert: NVIDIA's Scale Moat Relies on Amortizing 1,000+ CUDA Engineers Across Millions
“The whole CUDA investment. Not at first, but definitely now is predicated on being able to amortize that a thousand plus employees spend over the base of the three million developers and all the people who are buying the hardware to use what those developers c…”