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Is there really a need for 20gb of ram in a GPU?

ChuckNorris89 7y ago
Machine learning, data scientist and real time professional simulations. You need to have your models in video ram to be able to "play" with them in real time so with 20Gigs they can access larger models.
- samplatt 7y ago
  >Machine learning, data scientist and real time professional simulations. With photogrammetry (my field) we need to process anywhere between 1GB and 500GB of DSLR photos in one project and triangulate points between all these photos. Lots of RAM helps. Lots of VRAM helps JUST as much. Also crypto mining takes advantage of large VRAM too.
pacetherace 7y ago
May not be required for gaming but for their GPGPU market that is going to be a big win. Another use case is the Cloud gaming market where a single GPU needs to serve multiple users.
deleted 7y ago
[deleted]
btian 7y ago
Absolutely. Being able to train with larger batch size helps a lot with performance
nl 7y ago
Google recently released their Performer architecture paper where one of the major achievements was making it work within 16GB. More headroom is incredibly useful!
Pfhreak 7y ago
Need? Who knows. Do customers want it for various reasons? Absolutely. 4k and 8k gaming are definitely going to be a thing. Those textures are pretty big. (I think Final Fantasy XV is like 80GB larger if you get the 4k textures?)
- wruza 7y ago
  The article says that it is unlikely for consumer cards to get 20gb. The same chips go to pro-level cards, and they will have it. As far as I know from the latest gossip and tech details, 4k textures pretty much fit 8gb, and 4k gaming still struggles with 60fps, which 3840 cores will not change by a large margin. From that, 8k is simply a marketing move (apart from eye physics). Also, 4k/144 requires an active cooling of a monitor, and these still cost too much to become mainstream in 30xx lifetime. 8k is basically 4k x4, do the math.
bananamerica 7y ago
Maybe for real-time previews for video compositing such as Adobe After Effects?
spectramax 7y ago
YES! For rendering medium-large scenes in GPU based rendering engines such as Octane, Redshift, Arnold, etc. Take a sportscar sample model with good resolution, say 250k polygons. If you want to create an animation with 100 cars crashing into each other, you'll need a lot of GPU RAM.
Hamuko 7y ago
I imagine at least a part of that is because gamers want to see new hardware have bigger numbers than the old hardware and RAM is a pretty easy metric. RTX 2080s have 8-11 GB.
- james_s_tayler 7y ago
  1080ti GTX models also have around 11gb.
ksec 7y ago
Comparatively speaking Memory is cheap, I wish they started offering 32GB, 64GB or even 128GB for professional applications. I could start playing around with GPGPU Database.
- m0zg 7y ago
  HBM is not cheap. And for that throughput to be feasible, it also needs to be in close proximity as well.
  - ksec 7y ago
    Well that is HBM, not GDDR. And price / value differs to each individuals. Example the GeForce RTX 2080 Ti is only $1099. A Chip that is nearly 800mm2 die size. Pretty damn good if you ask me. They could have bump the Memory to 32GB and charge me $1500 which would give them even higher margin. I hope that is something AMD would do, pushing more Cores in CPU, pushing more Graphics Memory in GPU, let the developer figure out how to best use it.
    - AstralStorm 7y ago
      The slight problem is space on die. Higher density GDDR6 just don't exist, and attempting to connect more chips quickly runs into die size limitations and routing problems.
kavalg 7y ago
For Machine Learning (esp. computer vision) it is really important. First, as others have pointed out, it lets you use bigger batches of data in a single forward pass. This has not only performance aspects, but also certain regularization aspects. Second, if you want/need to use higher resolution inputs then you really need a lot of memory. For example, MaskRCNN - a popular instance segmentation network - can only do batch_size=1 at 960x960 pixel images (with some tweaks). 960x960 is not a particularity high resolution by contemporary standards and also a batch_size=1 can cause gradient fluctuations (this is usually not desired). There is also some trend in NLP (Natural Language) to work with lots of data/bigger models that are memory hungry (e.g. GPT-2).
Entalpi 7y ago
In the future, yes. As screen resolution increases a lot of textures increase as well. These mostly does not scale linearly as well so a large increase is to be expected from higher resolutions.
tromp 7y ago
The cuckatoo_mean_cuda_rtx_32 solver for Grin's Cuckatoo32 proof-of-work needs that much memory. This PoW is actually intended for ASICs, that would need only 512MB of SRAM with a different approach, but those ASICs have yet to appear.
thedaemon 7y ago
3d artist here, yes Renderer can use your GPU RAM while rendering.
kelsolaar 7y ago
It is common in VFX these days to have scenes that take well over 128Gb of RAM to render, 20Gb is, unfortunately, still quite thin :)

Machine learning, data scientist and real time professional simulations. You need to have your models in video ram to be able to "play" with them in real time so with 20Gigs they can access larger models.

samplatt 7y ago
>Machine learning, data scientist and real time professional simulations. With photogrammetry (my field) we need to process anywhere between 1GB and 500GB of DSLR photos in one project and triangulate points between all these photos. Lots of RAM helps. Lots of VRAM helps JUST as much. Also crypto mining takes advantage of large VRAM too.

pacetherace 7y ago

May not be required for gaming but for their GPGPU market that is going to be a big win. Another use case is the Cloud gaming market where a single GPU needs to serve multiple users.

deleted 7y ago

[deleted]

btian 7y ago

Absolutely. Being able to train with larger batch size helps a lot with performance

nl 7y ago

Google recently released their Performer architecture paper where one of the major achievements was making it work within 16GB. More headroom is incredibly useful!

Pfhreak 7y ago

Need? Who knows. Do customers want it for various reasons? Absolutely. 4k and 8k gaming are definitely going to be a thing. Those textures are pretty big. (I think Final Fantasy XV is like 80GB larger if you get the 4k textures?)

wruza 7y ago
The article says that it is unlikely for consumer cards to get 20gb. The same chips go to pro-level cards, and they will have it. As far as I know from the latest gossip and tech details, 4k textures pretty much fit 8gb, and 4k gaming still struggles with 60fps, which 3840 cores will not change by a large margin. From that, 8k is simply a marketing move (apart from eye physics). Also, 4k/144 requires an active cooling of a monitor, and these still cost too much to become mainstream in 30xx lifetime. 8k is basically 4k x4, do the math.

bananamerica 7y ago

Maybe for real-time previews for video compositing such as Adobe After Effects?

spectramax 7y ago

YES! For rendering medium-large scenes in GPU based rendering engines such as Octane, Redshift, Arnold, etc. Take a sportscar sample model with good resolution, say 250k polygons. If you want to create an animation with 100 cars crashing into each other, you'll need a lot of GPU RAM.

Hamuko 7y ago

I imagine at least a part of that is because gamers want to see new hardware have bigger numbers than the old hardware and RAM is a pretty easy metric. RTX 2080s have 8-11 GB.

james_s_tayler 7y ago
1080ti GTX models also have around 11gb.

ksec 7y ago

Comparatively speaking Memory is cheap, I wish they started offering 32GB, 64GB or even 128GB for professional applications. I could start playing around with GPGPU Database.

m0zg 7y ago
HBM is not cheap. And for that throughput to be feasible, it also needs to be in close proximity as well.
- ksec 7y ago
  Well that is HBM, not GDDR. And price / value differs to each individuals. Example the GeForce RTX 2080 Ti is only $1099. A Chip that is nearly 800mm2 die size. Pretty damn good if you ask me. They could have bump the Memory to 32GB and charge me $1500 which would give them even higher margin. I hope that is something AMD would do, pushing more Cores in CPU, pushing more Graphics Memory in GPU, let the developer figure out how to best use it.
  - AstralStorm 7y ago
    The slight problem is space on die. Higher density GDDR6 just don't exist, and attempting to connect more chips quickly runs into die size limitations and routing problems.

kavalg 7y ago

For Machine Learning (esp. computer vision) it is really important. First, as others have pointed out, it lets you use bigger batches of data in a single forward pass. This has not only performance aspects, but also certain regularization aspects. Second, if you want/need to use higher resolution inputs then you really need a lot of memory. For example, MaskRCNN - a popular instance segmentation network - can only do batch_size=1 at 960x960 pixel images (with some tweaks). 960x960 is not a particularity high resolution by contemporary standards and also a batch_size=1 can cause gradient fluctuations (this is usually not desired). There is also some trend in NLP (Natural Language) to work with lots of data/bigger models that are memory hungry (e.g. GPT-2).

Entalpi 7y ago

In the future, yes. As screen resolution increases a lot of textures increase as well. These mostly does not scale linearly as well so a large increase is to be expected from higher resolutions.

tromp 7y ago

The cuckatoo_mean_cuda_rtx_32 solver for Grin's Cuckatoo32 proof-of-work needs that much memory. This PoW is actually intended for ASICs, that would need only 512MB of SRAM with a different approach, but those ASICs have yet to appear.

thedaemon 7y ago

3d artist here, yes Renderer can use your GPU RAM while rendering.

kelsolaar 7y ago

It is common in VFX these days to have scenes that take well over 128Gb of RAM to render, 20Gb is, unfortunately, still quite thin :)