Falcon

A configuration recommender system for deep learning inference services.

Requirements

1. Linux OS (e.g., CentOS, RedHat, Ubuntu).
2. Docker >= 20.10.12.

How To

Step 1: pull docker image

docker pull frankwu2016/falcon:latest

Step 2: run docker container runtime

docker run -it frankwu2016/falcon:latest /bin/bash

Step 3: execute falctl command

1) The falctl evaluate command

Evaluate all DL models. Note that, the maximum number of iterations is 30.

falctl evaluate --all

(Optional) Evaluate a particular DL model. Note that, the maximum number of iterations is 30.

falctl evaluate --model [model-name]

Supported DL models: [bert-large|densenet-201|gru|inception-v2|inception-v4|mobilenet-v2|resnet-101|resnet-152-v2|roberta|tacotron2|transformer|vgg16]

2) The falctl analyze command

(Optional) Analyze a particular DL model.

falctl analyze --model [model-name]

Supported DL models: [bert-large|densenet-201|gru|inception-v2|inception-v4|mobilenet-v2|resnet-101|resnet-152-v2|roberta|tacotron2|transformer|vgg16]

(Optional) Analyze a particular DL operator.

falctl analyze --operator [operator-name]

Supported DL operators: [add|batch_norm|concat|conv1d|conv2d|dense|multiply|relu|sigmoid|split|strided_slice|tanh|transpose]

Step 4: check the results

1) Experimental data

Experimental outputs.

/home/falcon/data/[name].output

Experimental results.

/home/falcon/data/experiments/[name]-[model name].csv

2) Source data

Model's data. Please check the following directory.

/home/falcon/data/models/

Opeartor's data. Please check the following directory.

/home/falcon/data/operators/

3) Log file

Please check the following log file.

/var/log/falcon.log

License

Our implementation is released under Apache License 2.0 license except for the code derived from TuRBO.