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sofa

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SOFA: A Cross-framework Performance Profiler for Heterogeneous Computing Systems and Distributed Machine Learning Systems.

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# Community
[SOFA on Slack](https://sofa-cnj2673.slack.com)

# Introduction
SOFA: A Cross-framework performance profiler for heterogeneous computing systems, especially for HPC and distributed machine learning systems.

![Alt text](https://raw.githubusercontent.com/cyliustack/sofa/master/figures/sofa.png) 
    
# 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)
    * [http://localhost:8000/cpu-report.html](http://localhost:8000/cpu-report.html)
    * [http://localhost:8000/gpu-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"`   
![Alt text](https://raw.githubusercontent.com/cyliustack/sofa/master/figures/pytorch_resnet50.png)

`sofa record "./scout dt-bench ps:resnet50 --hosts='192.168.0.100,192.168.0.101'"`   
![Alt text](https://raw.githubusercontent.com/cyliustack/sofa/master/figures/sofa_network.png)

`sofa record "~/cuda_samples/1_Utilities/bandwidthTest/bandwidthTest"`  
![Alt text](https://raw.githubusercontent.com/cyliustack/sofa/master/figures/bandwidth.png)

`sofa record "./scout t-bench resnet50_real"`   
![Alt text](https://raw.githubusercontent.com/cyliustack/sofa/master/figures/realdata.png)

# Development and Contributions
We strongly encourage and appreciate any contributions to SOFA to make our performance engineering work more comfortable. 
But to maintain the quality of the codes, we need to regulate cooperations as the following:   
1. Please run `test/test.py` before sending pull request. If you want to test SOFA on some platforms, you could run `./test/test.py --dockerfiles Dockerfile.ubuntu.1604,Dockerfile.ubuntu.1804` where corresponding dockerfiles must be placed inside directory of test.

sofa

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