141–150 of 269 posts
NVIDIA is attempting to separate enterprise/datacenter and consumer chips to justify the cost disparity. Specifically, they're introducing memory, precision etc. limits which have major performance implications to GeForce and there's also the EULA which was been mentioned here. That said, everything AWS comes at a premium as they're making the case that on-demand scale outweighs the pain of management/CapEx. This pre…
Memory? Because if you can spread your model across multiple GPUs, and you've implemented Krizhevsky's One Weird Trick to switch between reducing the smallest of either parameters or deltas, you're golden.
I thought tensor cores and NVLINK would end up Tesla differentiators, and really great ones at that, but now they're both in the Turing consumer GPUs so I am really scratching my head here.
That said, the EULA is just stupid. I cannot use CUDA 9.2 or later at work because of it. No one is going to audit our computers for any reason ever, period, full stop.
> There’s one 1080 Ti GPU to start (you can just as easily use the new 2080 Ti for Machine Learning at $500 more — just be careful to get one with a blower fan design) I don't believe there are any blower-style 20-series cards. The reference cards use a dual-fan design.
Earlier quoted context omitted.
> Of course building is cheaper than AWS... Why "of course"? Last time I checked baking my own cookies is more expensive than just buying a bag at Walmart.
> Last time I checked baking my own cookies is more expensive than just buying a bag at Walmart. Yes, but most likely they aren't of comparable quality
https://www.amazon.com/NorthWest-Fork-Gluten-Free-Emergency-...
That drops to $1149 if I don't require Vegan, non-GMO, Kosher:
https://www.amazon.com/Healthy-Survival-Food-Emergency-Prepa...
SNAP benefits at anywhere from $134 to $192 a month are both more than sufficient for this. So why are ~42 million people starving in America? Answer (IMO): Cloud providers reduce the friction of GPU adoption the same way grocery and convenience stores reduce the friction of food acquisition, both in exchange for profiting off of it.
TL;DR: Proposed machine costs $3k plus ~$100-200?/month for electricity, comparable AWS is currently $3/hr.
My conclusion: If you're going to do more than 1-2,000hrs of GPU computing in the next few years, start thinking about building a machine.
Earlier quoted context omitted.
When I worked at Google, I really missed the dual monitor setup I had had at my previous job. I asked my manager how to get a 2nd monitor. Apparently, since I had the larger monitor, I was not allowed to get a 2nd one without all kinds of hassle. I asked if I was allowed to just buy one from Amazon and plug it in, and I was told no. I finally just grabbed an older one that had been sitting in the hallway of the cube-…
Wow, no dual/triple monitor setup is just uncivilized.
Of course building is cheaper than AWS... It also means you need to build the computer, maintain it, upgrade it, store it somewhere, connect it to the internet, and so on. And you can't just scale it if you need to. I mean, the cloud's here for a reason...
> Of course building is cheaper than AWS... Why "of course"? Last time I checked baking my own cookies is more expensive than just buying a bag at Walmart.
The answer is not clear cut!
Also, look into using S3 for long-term storage, instead of leaving your stuff cold in EBS volumes. It's quite a bit cheaper.
NVIDIA is attempting to separate enterprise/datacenter and consumer chips to justify the cost disparity. Specifically, they're introducing memory, precision etc. limits which have major performance implications to GeForce and there's also the EULA which was been mentioned here. That said, everything AWS comes at a premium as they're making the case that on-demand scale outweighs the pain of management/CapEx. This pre…