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Nvidia Announces A100 80GB GPU for AI
- hn3333 6y agoDoes processing power translate to actual power? Will most stock market gains in the end go to the people with the fastest computers? Will wars be won by the groups with the most processing speed? Was Cyberpunk (slightly) wrong and it's just about having more memory and more instructions per millisecond than the rest? Are sophisticated circuits the new oil?
- xiphias2 6y agoIsn't cyberpunk partly about companies having these most powerful tools to control (predict) people?
- smabie 6y agoWell I can answer the stock market question and the answer is a resounding no. Speed at this point is a commodity without a moat and brains are much more important than computational speed. If you're solely making money because you are fast.. well, you probably went out of business or you will soon. Anyone can spend money to be fast (speed is pure function of money spent). Great ideas are much harder come by. And while you can try and buy your way to the best ideas, it doesn't seem to work all that well.
- dasudasu 6y agoI was reading the latest earnings call transcript of this HFT firm Virtu Financial the other day, and it does appear to be that way. >So there is a back and forth here and all of the other players that we compete with, they are also economic animals. They don't have any magic elixir or magic algorithm that we don't have, right. We all kind of are doing the same thing and we're all providing great service and value for the marketplace. So I know this a little handy way to give an answer but there is an ebbs and flows around competition. The business continues to be very profitable for us on a net basis. On a gross basis it's incredibly profitable but as I said in my remarks, we have paid, put that in quotes, not in our financials we've provided back to our retail customers about $950 million of price improvement this year. https://seekingalpha.com/article/4386120-virtu-financial-inc-virt-ceo-doug-cifu-on-q3-2020-results-earnings-call-transcript https://seekingalpha.com/article/4386120-virtu-financial-inc... Top quantitative firms like RenTec don't rely critically on speed or compute power, but rather on high quality data, which they've also said publicly.
- smabie 6y agoAlso Virtu is a dying market participant. They were flying high but then lost out. Probably why they're talking about providing price improvements instead of raking in cash.
- deleted 6y ago[deleted]
- teruakohatu 6y agoProcessing power is just a proxy for money+energy which equals power.
- john_moscow 6y agoI am more wondering why hasn't AMD massively invested into porting common ML frameworks to OpenCL. Nvidia has outrageous margins on their datacenter GPUs. They've even banned the use of lower-margin gamer-oriented GPU in datacenters [0]. Given that tensor arithmetic is essentially an easily abstractable commodity, I just don't understand why they don't offer a drop-in replacement. Most users won't care what hardware their PyTorch model runs on in the cloud. All that matters for them is dollars per training epoch (or cents per inference). This could be a steal for an alternate hardware vendor. [0] https://web.archive.org/web/20201109023551/https://www.digitaltrends.com/computing/nvidia-bans-consumer-gpus-in-data-centers/ https://web.archive.org/web/20201109023551/https://www.digit...
- psds2 6y agoRather than OpenCL they have invested in HIP which can target AMD or NVIDIA cards.
- slezyr 6y agoIt doesn't work on their new GPUs and many others. It's Linux only and etc.
- sorenjan 6y agoCan HIP run on AMD consumer Radeon cards? I'm trying to find the best option to write GPGPU code that runs on other people's machines with hardware I have no control over. I thought OpenCL would become the best way to write code that could run on all PCs and mobile phones, but from my research the GPGPU landscape looks more fragmented for each year.
- my123 6y agoNot officially supported... and no ROCm/HIP at all on Windows.
- BadInformatics 6y agoOpenCL is supported via ROCm on the new consumer GPUs now, so if the stars align HIP support might come too. The lack of announcements doesn't inspire much confidence though, especially compared to NVIDIA's always-on PR machine.
- vbezhenar 6y agoWhy do they still produce GPU rather than specialized ASIC for neural networks like Google does with their Tensor Processing Units?
- justicezyx 6y agoPractically, GPU is still way more generalized than TPU. For that reason, optimizing an algorithm on TPU is usually much trickier than GPUs. There are much more nuances because of the way TPU is designed. On the other hand, Google has good reason to hold back TPUs from general public, and instead only offer them on Cloud. That also contributes its limited use.
- ra7 6y ago> On the other hand, Google has good reason to hold back TPUs from general public, and instead only offer them on Cloud. What is the reason? Just competitive advantage for running Google level AI/ML workloads?
- justicezyx 6y agoMany reasons: 1. Technically, TPU is less generalized, making it publicly appealing requires too much engineering effort, which has very high risk of not paying off. Case in comparison: How AMD is not able to capitialize on GPU in Deep Learning despite more uniform architecture. 2. TPUs does have some advantage, that Google want to keep at its own possession. For example, Google would not want FB to easily copy TPUs. FB indeed very likely benefit from TPUs, as they are running similar business.
- shorts_theory 6y agoDoesn't Google sell TPUs in the Coral AI line of devboards? (https://coral.ai/products/dev-board https://coral.ai/products/dev-board)
- justicezyx 6y agoThat’s inference only.
- fxtentacle 6y agoWhile these are amazing performance numbers, I seriously wonder if all this expensive AI magic will be cost effective in the end. Their lead example is recommendation systems, but I can't say that I have received many good suggestions recently. Spotify and Deezer both suggest the chart hits, regardless of how often I dislike that kind of music. Amazon keeps recommending me tampons (I'm a guy) ever since I've had a coworking office with a female colleague in 2015. For all the data that they collect and all the AI that they pay for, these companies get very little revenue to show for it.
- lhoff 6y agoI could imagine thats a bias. That we just remember the bad examples when den recommendation was bad but not when it was good because we didn't make the connection. I'm asking myself that for quite some time. Do you use a tracking blocker. That could also be a reason why you get bad recommendations.
- franklampard 6y agoMy Spotify recommendation is amazing. I have been an Apple Music user, but I am subscribing to Spotify just for its recommendations.
- mottosso 6y agoWas about to say the same. Have been eagerly awaiting an updated "Discover Weekly" playlist every Monday for years and it keeps getting better.
- mattnewton 6y agoScrolled through the comments exactly for this. In addition to the discover weekly, I'll often make a new playlist of 5-10 similar songs I like to get another in the same vein, and it works very well for my decidedly not-chart-topping music preferences. Maybe there are some genres I don't listen to enough that it struggles with?
- semi-extrinsic 6y ago
- Rafuino 6y agoFor only the low low cost of everything in your bank account!
- faitswulff 6y agoJokes on them, there's nothing there!
- deleted 6y ago[deleted]
- ogre_codes 6y agoIt occurs to me that if anyone is going to release an ARM based CPU that is competitive with Apple, it's Nvidia. A Microsoft/ Nvidia partnership could create some pretty impressive Surface laptops, and if Nvidia were allowed to sell those CPUs to OEMs for other 2 in 1s or laptops, Microsoft might just get some traction on their ARM efforts.
- phs318u 6y agoLegit question: Why are these still called "GPU"s? Shouldn't they rightly be called "AIPU"s, or "IPU"s?
- nabla9 6y agoThey can be use used for anything related to numerical programming. They are GPGPUs https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units https://en.wikipedia.org/wiki/General-purpose_computing_on_g... There are processors that are designed only for DNN inference but A100 is not one of them.
- eigenvalue 6y agoThe workstation they announced in the press release [0] sounds and looks incredible. I'm sure it costs over $100k, but I wish that kind of case design and cooling system could be available at a more reasonable price point. I wonder how long it will take for a computer with the performance specs of the DGX Station A100 to be available for under $3,000. Will that take 5 years? 10 years? Based on the historical trends of the last decade, those estimates strike me as pretty optimistic. [0] https://www.nvidia.com/en-us/data-center/dgx-station-a100/ https://www.nvidia.com/en-us/data-center/dgx-station-a100/
- taf2 6y agoAny word on how expensive this board will be?
- sien 6y agoIt is amusing to see this so soon after a post on how workstations were dead : https://news.ycombinator.com/item?id=24977652 https://news.ycombinator.com/item?id=24977652 $US 200K for startling performance this time.
- derefr 6y agoWorkstations are dead. With this kind of CapEx, nobody’s going to be buying N machines with these in them for their entire team, with one card per seat, going mostly unused. They’re going to build a farm of them, or they’re going to rent time on a cluster of them. Either way, that’d make them “server cards”, not “workstation cards.”
- timc3 6y agoDefinitely not dead in certain areas - video, 3D, audio, CAD, certain research. And there is more of that work being done than ever.
- peter_d_sherman 6y ago>"The new A100 with HBM2e technology doubles the A100 40GB GPU’s high-bandwidth memory to 80GB and delivers over 2 terabytes per second of memory bandwidth."