31–40 of 40 posts
Enroot sounds interesting: https://github.com/NVIDIA/enroot It basically returns containers to their chroot origins, promising "no performance overhead." I'm looking forward to more posts on that.
Earlier quoted context omitted.
I was under the impression the 3090 is the Titan of this generation.
I was as well, until I saw the Linus Tech Tips review of it: the drivers are (were?) missing support for some Titan optimizations -- the Titan RTX significantly beat the 3090 for a few benchmarks. If the card doesn't have these optimizations, I would expect that an actual 30 series Titan is coming at some point... But the marketing has been really confusing, so who the hell knows.
Enroot sounds interesting: https://github.com/NVIDIA/enroot It basically returns containers to their chroot origins, promising "no performance overhead." I'm looking forward to more posts on that.
Another aspect, the "unprivileged "part sounds like an advantage over Docker, on par with podman and lxd etc.
Earlier quoted context omitted.
What is the price of electricity where you live? For me to pay as much as the card is worth in electricity, even running it continuously, it would take 11 years. Granted, electricity is exceedingly cheap here, but still, 11 years is a long time.
About $0.20/kWh here. Works out to $600 a year I think
Earlier quoted context omitted.
I was under the impression the 3090 is the Titan of this generation.
I was as well, until I saw the Linus Tech Tips review of it: the drivers are (were?) missing support for some Titan optimizations -- the Titan RTX significantly beat the 3090 for a few benchmarks. If the card doesn't have these optimizations, I would expect that an actual 30 series Titan is coming at some point... But the marketing has been really confusing, so who the hell knows.
Enroot sounds interesting: https://github.com/NVIDIA/enroot It basically returns containers to their chroot origins, promising "no performance overhead." I'm looking forward to more posts on that.
What performance overhead does this avoid compared to other container runtimes? Another aspect, the "unprivileged "part sounds like an advantage over Docker, on par with podman and lxd etc.
Earlier quoted context omitted.
I was as well, until I saw the Linus Tech Tips review of it: the drivers are (were?) missing support for some Titan optimizations -- the Titan RTX significantly beat the 3090 for a few benchmarks. If the card doesn't have these optimizations, I would expect that an actual 30 series Titan is coming at some point... But the marketing has been really confusing, so who the hell knows.
Not only that they gimped the tensor cores. While it has way more shading units it only has 60% of the tensor cores that the Titan RTX has. I'm not sure how much of a difference this makes in practice, but it leads me to believe this is not the titan level card.
Earlier quoted context omitted.
What performance overhead does this avoid compared to other container runtimes? Another aspect, the "unprivileged "part sounds like an advantage over Docker, on par with podman and lxd etc.
What's the advantage of enroot over charliecloud, which is unprivileged in the sense of being installable in your home directory (given user namespaces)? https://hpc.github.io/charliecloud/
Enroot sounds interesting: https://github.com/NVIDIA/enroot It basically returns containers to their chroot origins, promising "no performance overhead." I'm looking forward to more posts on that.
What performance overhead does this avoid compared to other container runtimes? Another aspect, the "unprivileged "part sounds like an advantage over Docker, on par with podman and lxd etc.
You can read his analysis here: https://timdettmers.com/2020/09/07/which-gpu-for-deep-learni...
and his tweet about this here: https://twitter.com/Tim_Dettmers/status/1311354118514982912
Essentially from my understanding it's memory bandwidth which is the real critical path on performance in most cases. The previous generation of Turing cards had more compute than was necessary so they were an underutilized resource.
Also, this Puget benchmark is using an older version of the CUDA drivers. I believe performance is much better in CUDA 11.1.
This new benchmark which is running on the latest CUDA seems to confirm Tim's numbers: https://www.evolution.ai/post/benchmarking-deep-learning-wor...