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TuringBench Examples

Each of these examples follows the step by step procedure described on the homepage of this site.

Example 1: A Simple TuringBench Example

Topics covered:

  1. Getting started with the TuringBench workflow and Docker
  2. Creating benchmarks that can be run in a Docker container
  3. Benchmarking multiple versions of software with differently tagged versions of a Docker container

The GitHub repository for this example can be found at https://github.com/edwardchalstrey1/scikit-learn-classifier

Example 2: Benchmarking on GPU with NVIDIA-Docker

Topics covered:

  1. Running benchmark containers on different computing platforms
  2. Using nvidia-docker for running containers on GPU
  3. Creating a benchmark script with command line arguments to run alternate benchmarks with a single container

The GitHub repository for this example can be found at https://github.com/edwardchalstrey1/neural-network-julia-gpu

Example 3: High Performance Linpack Benchmark

Topics covered: Comparing the performance of different computing platforms with the Linpack Benchmark, by running this in a Docker container

The GitHub repository for this example can be found at https://github.com/edwardchalstrey1/high-performance-linpack

Example 4: Platform Agnostic Development with Docker and Singularity

Topics covered:

  1. Running benchmarks with Docker containers
  2. Building a Singularity image from a Docker image
  3. Running benchmark containers on HPCs
  4. Good practices for container use

Example 5: Running code that requires CUDA enabled GPUs on multiple platforms

Topics covered:

  1. Creating a CUDA enabled image for containers that run code on GPUs with Docker
  2. Building a CUDA enabled Singularity image from that Docker image with Singularity Hub
  3. Running these containers on different platforms, including HPCs