We need some competition to keep prices low and innovation high medium to long term.
We need some competition to keep prices low and innovation high medium to long term.
Given AMD's market cap and financial success, I bet they're working on competitive designs now. There's no money in being an also ran in the space.
I'd really urge anyone wanting to opine on these issues to watch the official analyst day videos and read through the releases AMD has put out so far in terms of architecture and other tech decisions they've made: https://www.youtube.com/watch?v=LMNwLVJQzGs&t=10064s
Ceiling fans are another great option for homogenizing the temperature of a room.
You don't need to build your climate control systems specifically with a PC in mind, they're designed to be adjusted.
AMD often has very high FLOPS but fails to translate that in to FPS in games, due to architecture inefficiency, drivers, or developers simply optimizing primarily for GeForce.
I would in turn urge you to take all of these figures with a large grain of salt until the third party benchmarks hit.
I guess it depends on what benchmark you care about but for AMD to compete with a 3080, which is 70-100% faster than a 2080, which is 10-20% faster than AMD's current flagship, they need to do a lot better than +50%.
"30% Faster Than The RTX 2080 Ti & 50% Faster Than the RTX 2080 SUPER on Average"
https://wccftech.com/nvidia-geforce-rtx-3080-graphics-card-b...
DLSS 1.9 was impressive, but has its problems and would understandably be avoided by most gamers. DLSS 2 is a whole different story[1], and is highly likely to be something that most gamers enable. 4K/60 or 1440p/240 are the golden standards for PC gamers (depending on whether you prefer high resolution, or high framerates) and DLSS 2 would help you achieve either.
RTX is nice, Minecraft RTX has done a lot for marketing it. Probably still a coin-flip on whether a gamer would eat the performance hit for the quality improvement.
Note that DLSS 2.0's model is not game specific ( https://www.nvidia.com/en-us/geforce/news/nvidia-dlss-2-0-a-... )
DLSS support is still game specific as it needs additional data beyond just the color buffer to do the up-scaling, such as motion vectors, but it at least doesn't need the expensive part that put it out of reach of eg. indie games.
So it's now on the "if unity & unreal support it, you'll see everyone have it in a few years" trajectory. Probably, anyway, similar to things like TXAA & FXAA.
Those are $1200+ monitors at any decent resolution.
EDIT: by resolution I mean the horizontal dimension of the monitor, where pc enthusiasts typically go for 27+ inches in width which are more expensive as you scale in size, add a curve, etc.
https://www.amazon.com/gp/product/B00SHZSXVI/ref=asin_title?...
No gsync/freesync, but I wasn't intending to game on it anyway.
There appears to be no FPS performance gain going from 144hz to 240hz though so you don't have to get crazy.
https://store.steampowered.com/hwsurvey/Steam-Hardware-Softw...
The chart toppers are the mid range cards (1060, 1050 Ti, 1050), exactly as you'd expect. But what you then might not expect is that the 1070 and 1080 are both still higher than any AMD offering. There's almost as many 2070 SUPER's ($600) as there are RX 580s ($230 @ launch, currently sub-$200), AMD's most popular GPU among Steam users.
Final perf numbers are being speculated as being “close to 3080” in the chip forums, but I’d take that with a grain of salt since those are rumors alone.
Intel is vulnerable. Now is the time for AMD to strike!
AMD has spent nearly its entirely life in second place as the resident "also ran". But they're still around...
Nvidia has settled on CUDA, and has maintained 13 years of compatibility. If SYCL is going to ever compete with CUDA, it's going to need to stick around long enough for people to build on it.
Edit: Also, SYCL should be supported by most things already supporting OpenCL, like Tensorflow for example.
CUDA's single-source environment is very good compared to SYCL or OpenCL. OpenMP still has single-source (just #pragma target), and is already adopted by the HPC crowd for multithreaded programming. NVidia and AMD support seems to be growing, especially because OpenMP is important to the supercomputer folks. (Summit and Frontier)
ROCm is CUDA-like and mostly works. The main issue is that CUDA will always remain a few steps ahead as AMD is forced to play "catchup". (ex: Cooperative groups are useful but unimplemented for now in ROCm). ROCm's main issue is being stuck in Linux, they need some Windows support if they want ROCm to really take off.
Maybe things have changed massively very recently, but I came back from iwocl (the OpenCL and SYCL conference) two years ago massively disappointed. And I still don't see anyone in the slice of the HPC space I'm familiar with (environmental & GIS-related modeling) using it, for a reason I presume.
https://software.intel.com/content/www/us/en/develop/tools/o... https://github.com/intel/llvm/blob/sycl/sycl/doc/GetStartedG... https://www.alcf.anl.gov/support-center/training-assets/road...
ROCm is a bit uneven with what cards it supports. Ex: Rx 550 never was supported (even though Polaris, the rest of the 5xx series worked). It seems like the only cards ROCm works for are the ones that share a chip and/or driver with AMD's "Machine Intelligence" line of cards. (MI50, MI60, etc. etc.). Which are Fiji (Rx Fury), Polaris (Rx 580), Vega, and Radeon VII.
CUDA is a "works on all NVidia devices" kind of thing. So I think people are surprised when they have to read the docs for AMD's ROCm.
14 months after release, still unsupported. AMD needs to step up to the plate if they want to be seriously considered in the AI world.
Because MI8 and Rx Fury have similarities, AMD gives ROCm support to both. Ditto with MI25 and Vega, and MI6 and Rx 580.
EDIT: With "Navi" gaining features in ROCm repos, my bet is that a new MI-card based on RDNA2 might be coming out soon. Maybe its Arcturus (the Exascale GPU for the Frontier supercomputer).
Is this really the case? Last I checked all the major Deep Learning toolsets ran off CUDA/cuDNN and there was nothing comparable for AMD hardware.
If you know where to look (i.e. it's public but unannounced) you can see that nightly wheels have been built for the last few days. So I would expect that some time between now and the Developer Day in November we'll see ROCm appear on PyTorch's "get started" page.