Enviornment Installation

• Install Anaconda3
• For setting up the enviornment run :
  • for instantiating with localstack: bash scripts/create_experiment_env_linux.sh srtml-exp localstack_init
  • for instantiating without localstack: bash scripts/create_experiment_env_linux.sh srtml-exp
  • Finally

         conda activate srtml-exp
         python -c "import srtml; srtml.init()"
    

Model Repository

Commands

• cleanmr: Cleans the model repository
• lsmr: lists the model repisotory
• plsmr: specify s3 uri and dive deeper into model repository tree

Experiment1 - Prepoc

One end-to-end running example of image preproc

Commands

For any command run <cmd> --help to get inputs

• prepoc_profile: profile the vertices given from a config file. Config files look like :

      [
         {
             "Model Name": "resnet50",
             "Accuracy": 75.8
         },
         {
             "Model Name": "resnet34",
             "Accuracy": 75.8
         }
      ]
  

• prepoc_populate: puts the profiled models into model repository

• prepoc_configure: configures the virtual abstract image classification model based on arrival curve config. Config looks like

      [
         {
             "mu (qps)": 100.0,
             "cv": 0,
             "# requests": 2000,
             "Latency Constraint (ms)": 100.0,
             "Planner": "SimulatedAnnealing"
         }
      ]
  

• prepoc_provision: provisions the configured models to get latency, throughput information

Demo

prepoc_profile
prepoc_populate
prepoc_configure
prepoc_provision

ls image_preprocessing/two_vertex/accuracy_degradation/virtual/virtual_image_classification.xlsx
ls image_preprocessing/two_vertex/accuracy_degradation/physical/image_classification.xlsx