<p>I am currently using Nvidia GTX1050 with 640 CUDA cores and 2GB GDDR5 for Deep Neural Network training. I want to buy a new GPU for training, but I am not sure how much performance improvement I can get.</p>

<p>I wonder if there is a way to roughly calculate the training performance improvement by just comparing GPUs' specification?</p>

<p>Assuming all training parameters are the same. I wonder if I can roughly assume the training performance improvement is X times because the CUDA core number and memory size increased X times?</p>

<p>For example, Is RTX2070 with 2304 CUDA cores and 8GB GDDR6 roughly 4 times faster than GTX1050? And is RTX2080Ti with 4352 CUDA cores and 11GB GDDR6 roughly 7 times faster than GTX1050?</p>

<p>Thanks.</p>

<training><gpu>
Can I calculate the training performance of GPUs by comparing their specification?
Lei Xun
# Can I calculate the training performance of GPUs by comparing their specification?

(Asked by: username_0 on 2019-04-08)

I am currently using Nvidia GTX1050 with 640 CUDA cores and 2GB GDDR5 for Deep Neural Network training. I want to buy a new GPU for training, but I am not sure how much performance improvement I can get.

I wonder if there is a way to roughly calculate the training performance improvement by just comparing GPUs' specification?

Assuming all training parameters are the same. I wonder if I can roughly assume the training performance improvement is X times because the CUDA core number and memory size increased X times?

For example, Is RTX2070 with 2304 CUDA cores and 8GB GDDR6 roughly 4 times faster than GTX1050? And is RTX2080Ti with 4352 CUDA cores and 11GB GDDR6 roughly 7 times faster than GTX1050?

Thanks.

**Tags:** training, gpu


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## 0 answers

