RTX remix works with the fixed function graphics pipeline. The Source engine supports DX7 renderer - for example in Half Life 2: https://www.anandtech.com/show/1549/9
Basically pre-SM 2.0 D3D9 games that don't use pixel shaders ...That would be weird. Doesn't RTX remix support DX9? Pardon me if the video explains this but I don't have time to watch currently.
Apple showed the benefits of unified memory the industry has no excuse now.. just imagine a rtx 5070 laptop with 80gb of vram ultra fastThe last question is very interesting, too. Unified memory is IMO the way to go on laptops, because unlike desktops, upgradeability is not important in that form factor while efficiency is super important. With desktop GPUs having higher and higher TGP, laptops will have to make perfect use of the closed system they have to come closer to desktop versions again, and I assume unified memory plays a crucial role here.
There's also another major advantage aside from efficiency. You can basically have as much VRAM as you want, because it's all shared memory, so if you configure your laptop with 64 or even 128 GB, you have way more VRAM than any desktop GPU will have even in the far future, so you theoretically never have to bother with video memory ever again in games and you can bascially run every machine learning task you wish. That is all under the condition that the RAM is fast enough of course, but the M1 Ultra proves LPDDRx something can deliver up to 800 GB/s bandwidth and more. Maybe with this design you can play for more than 1 hour on battery.
So yeah, this is definately the future for laptops and I look forward to buy a new gaming laptop with unified memory when it releases. I hope it will be soon, but I agree with Alex here that it requires the whole industry to come together so it might take a while. Intel and Nvidia for example have to create a high performance SoC that incorporates a high end i7 as well as a high performant RTX xx80 series GPU. Given this circurmstance, I suppose AMD is going the first to show true high performance SoCs in laptops as they produce CPU and GPU inhouse. Their 680m is already quite a capable iGPU.
Doesn't RDNA1 have DP4a?Really like the comparison at 35:10. Exactly as expected, Turing runs ML much faster than RDNA1 because of DP4a support, even before accounting for tensor core acceleration.
I assume this trend will continue when more and more ML in real time gets used in gaming!
The answer is no. RX 5700 is doing something other then DP4a to get XeSS to work and it shows.Doesn't RDNA1 have DP4a?
Or is it SM driver issues?
Doesn't RDNA1 have DP4a?
Or is it SM driver issues?
The last question is very interesting, too. Unified memory is IMO the way to go on laptops, because unlike desktops, upgradeability is not important in that form factor while efficiency is super important. With desktop GPUs having higher and higher TGP, laptops will have to make perfect use of the closed system they have to come closer to desktop versions again, and I assume unified memory plays a crucial role here.
There's also another major advantage aside from efficiency. You can basically have as much VRAM as you want, because it's all shared memory, so if you configure your laptop with 64 or even 128 GB, you have way more VRAM than any desktop GPU will have even in the far future, so you theoretically never have to bother with video memory ever again in games and you can bascially run every machine learning task you wish. That is all under the condition that the RAM is fast enough of course, but the M1 Ultra proves LPDDRx something can deliver up to 800 GB/s bandwidth and more. Maybe with this design you can play for more than 1 hour on battery.
So yeah, this is definately the future for laptops and I look forward to buy a new gaming laptop with unified memory when it releases. I hope it will be soon, but I agree with Alex here that it requires the whole industry to come together so it might take a while. Intel and Nvidia for example have to create a high performance SoC that incorporates a high end i7 as well as a high performant RTX xx80 series GPU. Given this circurmstance, I suppose AMD is going the first to show true high performance SoCs in laptops as they produce CPU and GPU inhouse. Their 680m is already quite a capable iGPU.
Apple showed the benefits of unified memory the industry has no excuse now.. just imagine a rtx 5070 laptop with 80gb of vram ultra fast
UMA is not a downgrade. The kind of LPDDRX used in M1 Ultra has similar low latency to DRAM but also provides super fast bandwidth for the GPU, it's the "eierlegende Wollmilchsau" as we say in German. There is no need for seperated pools anymore and UMA would result into unprecedented amounts of video memory, as the LPDDRX RAM is both high bandwidth GPU memory and low latency DRAM for the CPU at the same time.
This needs to happen and when it happens, it's glorious upgrade time for me.
Thought there was more to it, as this is to be expected.RDNA1 supports SM 6.4, which is what XeSS uses, but RDNA1 has run it without hardware DP4a support so it's slower (than a glacier).
UMA is not a downgrade. The kind of LPDDRX used in M1 Ultra has similar low latency to DRAM but also provides super fast bandwidth for the GPU, it's the "eierlegende Wollmilchsau" as we say in German. There is no need for seperated pools anymore and UMA would result into unprecedented amounts of video memory, as the LPDDRX RAM is both high bandwidth GPU memory and low latency DRAM for the CPU at the same time.
This needs to happen and when it happens, it's glorious upgrade time for me.
Yeah, I assume desktop PCs will continue this path and improving it.I'd prefer more of what we're currently getting in the PC space tbh which is ever closer integration between discrete CPU's and GPU's to bring the advantages of both UMA and separate dedicated processors under one umbrella. Things like resizable bar, smart access storage and HBCC are great examples of this. The tech just needs to become standardised so it can start being treated as the default by devs.