This is the code used for a few of the blog posts on: https://lambdalabs.com/blog including:
- 2080 Ti Deep Learning Benchmarks: https://lambdalabs.com/blog/2080-ti-deep-learning-benchmarks/
Environment:
- OS: Ubuntu 18.04
- TensorFlow version: 1.11.0-rc1
- CUDA Version 10.0
- CUDNN Version 7.3.0
Step One: Clone benchmark repo
git clone https://github.com/lambdal/lambda-tensorflow-benchmark.git --recursive
Step Two: Run benchmark
- Input proper gpu_indices (a comma seperated list, default 0) and num_iterations (default 10)
cd lambda-tensorflow-benchmark
./benchmark.sh gpu_indices num_iterations
Step Three: Report results
- Check the repo directory for folder <cpu>-<gpu>.logs (generated by benchmark.sh)
- Use the same num_iterations and gpu_indices for both benchmarking and reporting.
./report.sh <cpu>-<gpu>.logs num_iterations gpu_indices