https://docs.google.com/spreadsheets/d/1La55B-AVHSv9LiQcs6GM...
You can copy that spreadsheet and insert whatever system price (in kilodollars) you want into B15:F15. Hope this makes everybody's decision making easier.
As a system builder and AI research company, we're trying to make benchmarks that are scientific, reproducible, correlate with real world training scenarios, and have accurate prices.
1.75 / 1.36 (speed up of 2080 Ti over a single 1080 Ti) = 1.28. So expect 2x 1080 Ti to be about 30% faster.
You can see how multi-GPU training works with Titan V benchmarks in the link below. 1080 Ti have similar scaling profile.
https://deeptalk.lambdalabs.com/t/benchmarking-the-titan-v-v...
It's been a long time since GPU prices have been anywhere near MSRP, it seems dishonest to assume that they will be in the near future.
In the past, it has been common that new hardware with low initial supply fetched premiums that lasted until supply met demand. It's not dishonest to assume that it's the same case here.
While we could decide to write some software that could pull today's market prices and update tables and graphs dynamically, we just decided to settle on a single number. If you are settling on a single number, the choice is either market price on date of publication or MSRP. Given that other GPUs tend towards their MSRP as time goes on, we decided to choose MSRP.
By the way, the MSRP for a regular 2080Ti is 999$, the 1200$ is the Founder's Edition price.
GPU modules are manufactured in China. Their harmonized codes are covered in recently established tariffs. 10% tariffs are already hitting cards arriving at US ports. This tariff will increase to 25% on Jan 1.
Prices will stay well above MSRP.
1080 Tis are back under MSRP right now and have been for some time. We decided to assume that 2080 Tis would exhibit similar behavior.
Maybe in theory, but you can get a new 1080Ti for $700 while 2080Ti is impossible to get under $1200, which makes it 70% more expensive. At that point 2x 1080Ti sounds way better than 1x 2080Ti for Deep Learning to me (up to 22TFlops and 22GB of RAM).