kartdsam / sofa

SOFA (Swarm-Oriented Function Call Analysis)

Introduction

SOFA: SOFA (Swarm-Oriented Function Call Analysis) Authors: All the contributors of SOFA

Prerequisite

1. Run ./tools/prepare.sh to install all the necessary packages and python packages.
2. [OPTIONAL] Run ./tools/empower-tcpdump.sh $(whoami) to make network related events tracable in SOFA. After running this step, it is required to re-login to APPLY THE CHANGES!!!

Verify Permissions

Run the following simple tests to verify the permission settings of executing tcpdump under your permission.

• tcpdump -w sofa.pcap
• tcpdump -r sofa.pcap

Installation

1. Simply run ./install.sh </PATH/TO/INSTALL> to install SOFA on your system. Note that sofa will be appended to the path if the last directory is not sofa.
2. Then, run source </PATH/TO/INSTALL>/sofa/tools/activate.sh to activate SOFA running environment. (Need to be executed on each new shell.)
3. [ALTERNATIVE] Add source </PATH/TO/INSTALL>/sofa/tools/activate.sh in your ~/.bashrc to make this environment available on every shell.

Uninstall

Run bash </PATH/TO/INSTALL>/sofa/tools/uninstall.sh to safely remove/uninstall files of SOFA.

Usages

SOFA supports serveral different usages, like how one can use perf.

Basic Statistics

1. Profile your program by sampling involved CPUs:
   sofa stat "wget http://www.bbc.com/news"
2. Profile your program by sampling all CPUs:
   sofa stat "wget http://www.bbc.com/news" --profile_all_cpus

Performance Visualizations

1. sofa record "wget http://www.bbc.com/news"
2. sofa report
3. Open browser with one of the following links for different visualizations
   • http://localhost:8000
   • http://localhost:8000/cpu-report.html
   • http://localhost:8000/gpu-report.html

Run SOFA Module-by-module

1. Run sofa record "wget http://www.bbc.com/news" only once to record the events.
2. Run sofa preprocess only once to process raw performance data and generate immediate results.
3. Run sofa analyze performance statistics will be displayed on your console
4. Run sofa viz --viz_port=8000 dynamic trace will be displayed on port 8000 (default)

Configurations

SOFA provides options for configurations. Some examples are shown below. Please use sofa --help to see more info.

1. sofa --cpu_filters="idle:black,tensorflow:orange" record "python tf_cnn_benchmarks.py"
2. sofa --gpu_filters="tensorflow:orange" record "python tf_cnn_benchmarks.py"

Examples of Visualization Results:

sofa record "python3.6 pytorch_dnn_example.py -a resnet50 /mnt/dataset/imagenet/mini-imagenet/raw-data --epochs=1 --batch-size=64"

sofa record "./scout dt-bench ps:resnet50 --hosts='192.168.0.100,192.168.0.101'"

sofa record "~/cuda_samples/1_Utilities/bandwidthTest/bandwidthTest"

sofa record "./scout t-bench resnet50_real"