oranger239 / sofa

Swarm of Functions Analysis Tools

Introduction

SOFA: SOFA (Swarm-Oriented Function Call Analysis)

Prerequisite

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

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.

Usages

SOFA supports serveral different usages, like how one can use perf. More details can be seen in the following slide

• slide: https://docs.google.com/presentation/d/1fyNnLlU-0WMIddkI8hgYn0Tg1vbP9i7VuXSPIsXB2L4/edit?usp=sharing

Basic Statistics

1. Profile your program by sampling involved CPUs:
   sofa stat "dd if=/dev/zero of=dummy.out bs=100M count=10"
2. Profile your program by sampling all CPUs:
   sofa stat "dd if=/dev/zero of=dummy.out bs=100M count=10" --profile_all_cpus

Performance Visualizations

1. sofa record "dd if=/dev/zero of=dummy.out bs=100M count=10"
2. sofa report [--verbose] [--with-gui]
3. If passing "--with-gui" to "sofa report", you could 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

Advanced Usages

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

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

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"