README.md
October 16, 2018 ยท View on GitHub
This repository contains raw experimental results in the CK format for the image classification workflow from the ReQuEST tournament at ASPLOS'18 on reproducible SW/HW co-design of deep learning (speed, accuracy, energy, costs). The live ReQuEST scoreboard shows a subset of these results.
References
Installation
Minimal CK installation
The minimal installation requires:
- Python 2.7 or 3.3+ (limitation is mainly due to unitests)
- Git command line client.
You can install CK in your local user space as follows:
$ git clone http://github.com/ctuning/ck
$ export PATH=$PWD/ck/bin:$PATH
$ export PYTHONPATH=$PWD/ck:$PYTHONPATH
You can also install CK via PIP with sudo to avoid setting up environment variables yourself:
$ sudo pip install ck
Install this CK repository and dependencies
$ ck pull repo:ck-request-asplos18-results-caffe-intel
List available experiments
$ ck ls ck-request-asplos18-results-caffe-intel:experiment:*
Replay experiment
$ ck replay experiment:{name from above list}
Note that CK will try to automatically rebuild experimental setup by detecting already installed software dependencies and installing missing ones using shared CK packages.
If you want to have a software setup as close to the original one as possible, install packages before running replay as described in the ReadMe of the related CK workflow.
Start dashboard to visualize/compare results
$ ck dashboard request.asplos18 --results=ck-request-asplos18-results-caffe-intel