3 ms·
At what point do the OEMs begin to realize they don’t have to follow the current mindset of attaching a GPU to a PC and instead sell what looks like a GPU with
by Waterluvian 11mo ago
At what point do the OEMs begin to realize they don’t have to follow the current mindset of attaching a GPU to a PC and instead sell what looks like a GPU with a PC built into it?
- nightshift1 11mo agoExactly. With the Intel-Nvidia partnership signed this September, I expect to see some high-performance single-board computers being released very soon. I don't think the atx form-factor will survive another 30 years.
- bostik 11mo agoOne should also remember that NVidia does have organisational experience on designing and building CPUs[0]. They were a pretty big deal back in ~2010, and I have to admit I didn't know that Tegra was powering Nintendo Switch. 0: https://en.wikipedia.org/wiki/Tegra https://en.wikipedia.org/wiki/Tegra
- goku12 11mo agoI had a Xolo Tegra Note 7 tablet (marketed in the US as EVGA Tegra Note 7) in around 2013. I preordered it as far as I remember. It had a Tegra 4 SoC with quad core Cortex A15 CPU and a 72 core GeForce GPU. Nvidia used to claim that it is the fastest SoC for mobile devices at the time. To this day, it's the best mobile/Android device I ever owned. I don't know if it was the fastest, but it certainly was the best performing one I ever had. UI interactions were smooth, apps were fast on it, screen was bright, touch was perfect and still had long enough battery backup. The device felt very thin and light, but sturdy at the same time. It had a pleasant matte finish and a magnetic cover that lasted as long as the device did. It spolied the feel of later tablets for me. It had only 1 GB RAM. We have much more powerful SoCs today. But nothing ever felt that smooth (iPhone is not considered). I don't know why it was so. Perhaps Android was light enough for it back then. Or it may have had a very good selection and integration of subcomponents. I was very disappointed when Nvidia discontinued the Tegra SoC family and tablets.
- deleted 10mo ago[deleted]
- miladyincontrol 10mo agoI'd argue their current CPUs aren't to be discounted either. Much as people love to crown Apple's M-series chips as the poster child of what arm can do, Nvidia's grace CPUs too trade blows with the best of the best. It leaves one to wonder what could be if they had any appetite for devices more in the consumer realm of things.
- pjmlp 11mo agoSo basically going back to the old days of Amiga and Atari, in a certain sense, when PCs could only display text.
- goku12 11mo agoI'm not familiar with that history. Could you elaborate?
- pjmlp 11mo agoIn the home computer universe, such computers were the first ones having a programmable graphics unit that did more than paste the framebuffer into the screen. While the PCs were still displaying text, or if you were lucky to own an Hercules card, gray text, or maybe a CGA one, with 4 colours. While the Amigas, which I am more confortable with, were doing this in the mid-80's: https://www.youtube.com/watch?v=x7Px-ZkObTo https://www.youtube.com/watch?v=x7Px-ZkObTo https://www.youtube.com/watch?v=-ga41edXw3A https://www.youtube.com/watch?v=-ga41edXw3A The original Amiga 1000, had on its motherboard, later reduced to fit into an Amiga 500, Motorola 68000 CPU, a programmable sounds chip with DMA channels (Paula), and a programable blitter chip (Agnus aka early GPUs). You would build in RAM the audio, or graphics instructions for the respetive chipset, set the DMA parameters, and let them lose.
- estimator7292 10mo agoIn the olden days we didn't have GPUs, we had "CRT controllers". What it offered you was a page of memory where each byte value mapped to a character in ROM. You feed in your text and the controller fetches the character pixels and puts them on the display. Later we got ASCII box drawing characters. Then we got sprite systems like the NES, where the Picture Processing Unit handles loading pixels and moving sprites around the screen. Eventually we moved on to raw framebuffers. You get a big chunk of memory and you draw the pixels yourself. The hardware was responsible for swapping the framebuffers and doing the rendering on the physical display. Along the way we slowly got more features like defining a triangle, its texture, and how to move it, instead of doing it all in software. Up until the 90s when the modern concept of a GPU coalesced, we were mainly pushing pixels by hand onto the screen. Wild times. The history of display processing is obviously a lot more nuanced than that, it's pretty interesting if that's your kind of thing.
- animal531 11mo agoIt's funny how ideas come and go. I made this very comment here on Hacker News probably 4-5 years ago and received a few down votes for it at the time (albeit that I was thinking of computers in general). It would take a lot of work to make a GPU do current CPU type tasks, but it would be interesting to see how it changes parallelism and our approach to logic in code.
- goku12 11mo ago> I made this very comment here on Hacker News probably 4-5 years ago and received a few down votes for it at the time HN isn't always very rational about voting. It will be a loss if you judge any idea on their basis. > It would take a lot of work to make a GPU do current CPU type tasks In my opinion, that would be counterproductive. The advantage of GPUs is that they have a large number of very simple GPU cores. Instead, just do a few separate CPU cores on the same die, or on a separate die. Or you could even have a forest of GPU cores with a few CPU cores interspersed among them - sort of like how modern FPGAs have logic tiles, memory tiles and CPU tiles spread out on it. I doubt it would be called a GPU at that point.
- Den_VR 11mo agoAs I recall, Gartner made the outrageous claim that upwards of 70% of all computing will be “AI” in some number of years - nearly the end of cpu workloads.
- yetihehe 11mo agoLooking at home computers, most of "computing" when counted as flops is done by gpus anyway, just to show more and more frames. Processors are only used to organise all that data to be crunched up by gpus. The rest is browsing webpages and running some word or excel several times a month.
- deliciousturkey 11mo agoI'd say over 70% of all computing is already been non-CPU for years. If you look at your typical phone or laptop SoC, the CPU is only a small part. The GPU takes the majority of area, with other accelerators also taking significant space. Manufacturers would not spend that money on silicon, if it was not already used.
- themafia 11mo agoAt this point what you really need is an incredibly powerful heatsink with some relatively small chips pressed against it.
- whywhywhywhy 10mo agoTranshcan Mac Pro was this idea, triangular heatsink core cpu+gpu+gpu for each side
- jnwatson 10mo agoIf you disassemble a modern GPU, that's what you'll find. 95% by weight of a GPU card is cooling related.
- amelius 11mo agoMaybe at the point where you can run Python directly on the GPU. At which point the GPU becomes the new CPU. Anyway, we're still stuck with "G" for "graphics" so it all doesn't make much sense and I'm actually looking for a vendor that takes its mission more seriously.
- lizknope 10mo agoThe vast majority of computers sold today have a CPU / GPU integrated together in a single chip. Most ordinary home users don't care about GPU or local AI performance that much. In this video Jeff is interested in GPU accelerated tasks like AI and Jellyfin. His last video was using a stack of 4 Mac Studios connected by Thunderbolt for AI stuff. https://www.youtube.com/watch?v=x4_RsUxRjKU https://www.youtube.com/watch?v=x4_RsUxRjKU The Apple chips have both power CPU and GPU cores but also have a huge amount of memory (512GB) directly connected unlike most Nvidia consumer level GPUs that have far less memory.
- onion2k 10mo agoMost ordinary home users don't care about GPU or local AI performance that much. Right now, sure. There's a reason why chip manufacturers are adding AI pipelines, tensor processors, and 'neural cores' though. They believe that running small local models are going to be a popular feature in the future. They might be right.
- swiftcoder 10mo agoIt's mostly marketing gimmicks though - they aren't adding anywhere near enough compute for that future. The tensor cores in an "AI ready" laptop from a year ago are already pretty much irrelevant as far as inferencing current-generation models go.
- zozbot234 10mo agoNPU/Tensor cores are actually very useful for prompt pre-processing, or really any ML inference task that isn't strictly bandwidth limited (because you end up wasting a lot of bandwidth on padding/dequantizing data to a format that the NPU can natively work with, whereas a GPU can just do that in registers/local memory). Main issue is the limited support in current ML/AI inference frameworks.
- cmrdporcupine 10mo agoI mean, that's kind of what's going on at a certain level with the AMD Strix Halo, the NVIDIA GB10, and the newer Apple machines. In the sense that the RAM is fully integrated, anyways.
- not_the_fda 10mo agoThey already have. They have the Jetson Line: https://en.wikipedia.org/wiki/Nvidia_Jetson https://en.wikipedia.org/wiki/Nvidia_Jetson