8x NVIDIA Tesla V100 32GB PCIe Monero Mining Speed

Discussion in 'Cryptocurrency Mining and Markets' started by Patrick, Jan 5, 2019.

  1. Patrick

    Patrick Administrator
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    Since we already did the NVIDIA Tesla P100 16GB SXM2 Monero mining speed, I figured I would burn-in the 8x Tesla V100 system for 15 minutes with this before benchmarking. Using the same Docker container for both. Here are the results.

    Code:
    [2019-01-06 02:11:22] accepted (153/0) diff 100001 (65 ms)
    | THREAD | GPU | 10s H/s | 60s H/s | 15m H/s | NAME
    |      0 |   0 |     n/a |  1527.0 |  1527.0 | Tesla V100-PCIE-32GB
    |      1 |   1 |     n/a |  1526.8 |  1526.5 | Tesla V100-PCIE-32GB
    |      2 |   2 |     n/a |  1526.7 |  1526.7 | Tesla V100-PCIE-32GB
    |      3 |   3 |     n/a |  1524.1 |  1524.7 | Tesla V100-PCIE-32GB
    |      4 |   4 |     n/a |  1526.1 |  1526.0 | Tesla V100-PCIE-32GB
    |      5 |   5 |     n/a |  1526.2 |  1526.4 | Tesla V100-PCIE-32GB
    |      6 |   6 |     n/a |  1525.8 |  1526.4 | Tesla V100-PCIE-32GB
    |      7 |   7 |     n/a |  1526.9 |  1526.8 | Tesla V100-PCIE-32GB
    [2019-01-06 02:11:34] speed 10s/60s/15m n/a 12210.0 12211.0 H/s max n/a H/s
    
    What is really interesting here is that the Tesla P100 16GB SXM2 setup was essentially the same speed, but slightly faster. The SXM2 modules have higher TDP. Perhaps that helps. Power consumption of this server is 1.397kW versus 1.33kW on the Tesla P100 box, but the ~60W can be accounted for from the differences in configuration. Both systems are using 4x Delta brand 2.2kW power supplies that are 80Plus Platinum rated.

    Code:
    +-----------------------------------------------------------------------------+
    | NVIDIA-SMI 410.48                 Driver Version: 410.48                    |
    |-------------------------------+----------------------+----------------------+
    | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
    | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
    |===============================+======================+======================|
    |   0  Tesla V100-PCIE...  Off  | 00000000:3D:00.0 Off |                    0 |
    | N/A   59C    P0   119W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   1  Tesla V100-PCIE...  Off  | 00000000:3E:00.0 Off |                    0 |
    | N/A   59C    P0   120W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   2  Tesla V100-PCIE...  Off  | 00000000:40:00.0 Off |                    0 |
    | N/A   62C    P0   122W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   3  Tesla V100-PCIE...  Off  | 00000000:41:00.0 Off |                    0 |
    | N/A   57C    P0   119W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   4  Tesla V100-PCIE...  Off  | 00000000:B1:00.0 Off |                    0 |
    | N/A   58C    P0   116W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   5  Tesla V100-PCIE...  Off  | 00000000:B2:00.0 Off |                    0 |
    | N/A   58C    P0   123W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   6  Tesla V100-PCIE...  Off  | 00000000:B4:00.0 Off |                    0 |
    | N/A   61C    P0   121W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    |   7  Tesla V100-PCIE...  Off  | 00000000:B5:00.0 Off |                    0 |
    | N/A   58C    P0   119W / 250W |  31160MiB / 32480MiB |    100%      Default |
    +-------------------------------+----------------------+----------------------+
    
    You can see that the containers are using more memory, but that is not really yielding more performance.

    Looks like it is running this stable, so time for Resnet50 training.
     
    #1
    William likes this.
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