21–30 of 34 posts
The "I have almost no money" recommendation should include Colab. https://medium.com/deep-learning-turkey/google-colab-free-gp... Somebody who has almost no money isn't going to be able to equip a desktop with a GTX 1050 Ti ($175), fast disk ($50), and RAM ($50) on an entry level cpu/motherboard/power supply/case/monitor/peripherals ($300) and pay for the electricity used during training. Colab can be accessed from a…
The "I have almost no money" recommendation should include Colab. https://medium.com/deep-learning-turkey/google-colab-free-gp... Somebody who has almost no money isn't going to be able to equip a desktop with a GTX 1050 Ti ($175), fast disk ($50), and RAM ($50) on an entry level cpu/motherboard/power supply/case/monitor/peripherals ($300) and pay for the electricity used during training. Colab can be accessed from a…
We’ve benched the 1080Ti vs the Titan V and the Titan V is nowhere near 2x faster at training than the 1080Ti as suggested in that graph. We observed a 30% to 40% speedup during our benchmarking:
https://deeptalk.lambdalabs.com/t/benchmarking-the-titan-v-v...
This is consistent with the 32% increase in FP32 flops from 11.3TFlops for the 1080Ti to 15TFlops for the Titan V. Additional speedups can be explained by the increase in memory bandwidth for HBM2 and the mixed precision fused multiply adds provided by the TensorCores.
Thus, given the quoted 13Tflop numbers for the 2080Ti, I would expect the 2080Ti to present something more like a 15-20% speedup over the 1080Ti. So 2080Ti is less bang for your buck. But benchmarking is the only way to tell what’s better on a FLOPS/$ basis.
An open question for me is the performance of two 2080tis using NVLink as one virtual GPU. I imagine it’ll be close to linear, but I’ll be interested to know for sure.
The "I have almost no money" recommendation should include Colab. https://medium.com/deep-learning-turkey/google-colab-free-gp... Somebody who has almost no money isn't going to be able to equip a desktop with a GTX 1050 Ti ($175), fast disk ($50), and RAM ($50) on an entry level cpu/motherboard/power supply/case/monitor/peripherals ($300) and pay for the electricity used during training. Colab can be accessed from a…
What are the rules about datasets I upload to this free service? Do Google now own them?
The "I have almost no money" recommendation should include Colab. https://medium.com/deep-learning-turkey/google-colab-free-gp... Somebody who has almost no money isn't going to be able to equip a desktop with a GTX 1050 Ti ($175), fast disk ($50), and RAM ($50) on an entry level cpu/motherboard/power supply/case/monitor/peripherals ($300) and pay for the electricity used during training. Colab can be accessed from a…
The cost/performance plot - shouldn't it be "Lower is better"? It says "Higher is better". Lower value would indicate lower cost per unit level of performance. It should be "Lower is better" or the plot needs to say "Performance/Cost". Am I missing something?
The "I have almost no money" recommendation should include Colab. https://medium.com/deep-learning-turkey/google-colab-free-gp... Somebody who has almost no money isn't going to be able to equip a desktop with a GTX 1050 Ti ($175), fast disk ($50), and RAM ($50) on an entry level cpu/motherboard/power supply/case/monitor/peripherals ($300) and pay for the electricity used during training. Colab can be accessed from a…
The 2080Ti numbers are likely going to be a lot lower than that. We’ve benched the 1080Ti vs the Titan V and the Titan V is nowhere near 2x faster at training than the 1080Ti as suggested in that graph. We observed a 30% to 40% speedup during our benchmarking: https://deeptalk.lambdalabs.com/t/benchmarking-the-titan-v-v... This is consistent with the 32% increase in FP32 flops from 11.3TFlops for the 1080Ti to 15TFlo…
You also do not benchmark LSTMs: https://www.xcelerit.com/computing-benchmarks/insights/bench...
If you put both of those benchmarks together my conclusion is quite reasonable. But I see that you could also come to your conclusion with your benchmarks. It is just a question which benchmarks are less biased and that is too difficult to evaluate.
I guess we have to wait for real data, but thanks for putting your data out there to get a discussion going.