I have been getting restless to do another deep learning build. Today I invested in some Tesla P100 16GB GPUs.
Instead of going with PCIe cards, I decided SXM2 with NVLink.
Next items:
1. Need to do some research on whether I can put P100 in V100 trays. The V100 I believe has 6x 50gb/s links. The P100 was 4x 40. That is a big difference but if if they work with both, I will want the newer V100 trays.
2. I think this is going to be Skylake based. It looks like the E5 generations were less expensive because CPUs were less expensive. Also, motherboards were less expensive.
3. Skylake is somewhat strange. If you want 2x GPU memory, and each P100 has 16GB that is 64GB in a 4x GPU system or 128GB in an 8x GPU system. That means, at 2x is 128 or 256GB of system RAM. With Skylake the options are really 96GB, 192GB, or 384GB. With E5 128 or 256GB would be easier.
4. CPUs. What to use?
Many questions. Likely a few weeks from answers.
Instead of going with PCIe cards, I decided SXM2 with NVLink.
Next items:
1. Need to do some research on whether I can put P100 in V100 trays. The V100 I believe has 6x 50gb/s links. The P100 was 4x 40. That is a big difference but if if they work with both, I will want the newer V100 trays.
2. I think this is going to be Skylake based. It looks like the E5 generations were less expensive because CPUs were less expensive. Also, motherboards were less expensive.
3. Skylake is somewhat strange. If you want 2x GPU memory, and each P100 has 16GB that is 64GB in a 4x GPU system or 128GB in an 8x GPU system. That means, at 2x is 128 or 256GB of system RAM. With Skylake the options are really 96GB, 192GB, or 384GB. With E5 128 or 256GB would be easier.
4. CPUs. What to use?
Many questions. Likely a few weeks from answers.