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NVIDIA's Neural Texture Compression Cuts VRAM Use From 6.5 GB to 970 MB (www.techpowerup.com)
submitted 4 months ago by [M] to c/hardware@lemmy.world
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[–] 20 points 4 months ago (1 child)

Nvidia has always had strong real time hardware accelerated memory compression.

Compute is basically a free lunch compared to memory bottlenecks. And individual textures will probably fit in low level caches, which allows the compute to flex.

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  • [–] 2 points 4 months ago (1 child)

    doesn't that end up using more energy? I thought compute was more power intensive than accessing memory.

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  • [–] 2 points 4 months ago* (last edited 4 months ago)

    Compute units are significant, but so are the caches and i/o.

    Real world datasets tend to have a lot of sparsity.

    One of the biggest problems is called a page fault. Which is basically when the app needs to go to storage to find data to continue execution. This results in the processor waiting, which isn't free.

    Generally, I'd say they go hand in hand about 50/50 plus or minus 10%.

    One benchmarks can fit in L1 cache and really stress the cores but most benchmarks you're using all the levels of cache, ram, IO, etc... which is a hell of a lot compared to just a little bit of processor in that chip. GPUs again are often just massive collaborations of massive throughout and compute. So it can be to really separate.

    And legit. Most data is compressed these days on the Internet. So that's again compute used to save data in flight. It's a neverending tradeoff.

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