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