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- Instance type: NVIDIA® DGX-1™
- GPU: 8x NVIDIA® Tesla® P100
- OS: Ubuntu 16.04 LTS with tests run via Docker
- CUDA / cuDNN: 8.0 / 5.1
- TensorFlow GitHub hash: b1e174e
- Benchmark GitHub hash: 9165a70
- Build Command:
bazel build -c opt --copt=-march="haswell" --config=cuda //tensorflow/tools/pip_package:build_pip_package - Disk: Local SSD
- DataSet: ImageNet
- Test Date: May 2017
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- Instance type: IBM Power9, 8335-GTG AC922 server
- CPU: 2x 20-core IBM POWER9 CPU @ 2.00GHz
- SDRAM: 512G DDR4
- GPU: 4x NVIDIA® Tesla® V100, 5120 cores, 16 GB HBM 2
- Disk: Local SSD
- OS: Red Hat Enterprise Linux Server release 7.4
- Python Distribution: Anaconda python 3.6.2
- CUDA / cuDNN: 9.1/7.0.5
- TensorFLow Version: 1.5.0
- DataSet: ImageNet (synthetic)
- Precision: floating point 32 and 16
- Test Date: Mar 25 2018
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