Real Performance Comparison: H100 vs RX 6000 Ada
Hi,
I’m experiencing some confusion or perhaps misunderstanding regarding the performance of the H100 and RX 6000 Ada GPUs during model training.
Lately, I’ve been working with both GPUs to train a model using 9 GB of training data and 8 GB of testing data. The model has 2.6M parameters.
On the RX 6000 Ada, I’m observing an average speed of around 200 ms/step in my current tests:
Epoch 2/15
601/1427 ━━━━━━━━━━━━━━━━━━━━ 2:41 195ms/step - binary_accuracy: 0.8878 - loss: 0.2556
yesterday using the h100 i was having more than 300ms/step... somethings 400ms/step and rarely 200ms/step.
With the same script, same date, same everything.
Are the H1000 and RX6000 ada the same thing ?
Regards.
I’m experiencing some confusion or perhaps misunderstanding regarding the performance of the H100 and RX 6000 Ada GPUs during model training.
Lately, I’ve been working with both GPUs to train a model using 9 GB of training data and 8 GB of testing data. The model has 2.6M parameters.
On the RX 6000 Ada, I’m observing an average speed of around 200 ms/step in my current tests:
Epoch 2/15
601/1427 ━━━━━━━━━━━━━━━━━━━━ 2:41 195ms/step - binary_accuracy: 0.8878 - loss: 0.2556
yesterday using the h100 i was having more than 300ms/step... somethings 400ms/step and rarely 200ms/step.
With the same script, same date, same everything.
Are the H1000 and RX6000 ada the same thing ?
Regards.
