Fibertree/Timeloop/Accelergy Tutorial

Infrastructure Installation Instructions for
Timeloop/Accelergy and Sparse Tensor Accelerators Tutorials


Infrastructure Installation Instructions

This tutorial involves hands-on exercises and labs. In order to follow our interactive live session better, please follow the instructions for installing the necessary infrastructure and exercises. It's even better if you can go through the exercises before the tutorial session and be ready with questions.

Option1: Installation with Docker (docker app required)

To install the tutorial docker:
  1. If you do not have the docker app installed already, please install docker (community edition)
  2. (Windows users - please manually turn on virtualization via BIOS settings.)
  3. Go to our tutorial exercises repo and follow instructions under `Using Docker`

Option2: Native Installation on Linux/Unix System

Please follow to following instructions to manually install the required tools and tutorial exercises:

Debug Tip: depending on your system, tools might be installed into other directories than ~/.local, you can find out where Accelergy and its plug-ins are installed by which accelergy -- if different, replace all the ~/.local in the paths with your own installation prefix.

  • sudo apt install scons libconfig++-dev libboost-dev libboost-iostreams-dev libboost-serialization-dev libyaml-cpp-dev libncurses-dev libtinfo-dev libgpm-dev git build-essential python3-pip
  • mkdir timeloop-accelergy
  • cd timeloop-accelergy
  • git clone --recurse-submodules
  • cd accelergy-timeloop-infrastructure
  • make pull
  • cd src/cacti
  • make
  • cd ../accelergy
  • pip3 install --upgrade pip
  • pip3 install .
  • cd ../accelergy-aladdin-plug-in/
  • pip3 install .
  • cd ../accelergy-cacti-plug-in/
  • pip3 install .
  • cp -r ../cacti ~/.local/share/accelergy/estimation_plug_ins/accelergy-cacti-plug-in/
  • cd ../accelergy-table-based-plug-ins/
  • pip3 install .
  • cd ../timeloop
  • cd src/
  • ln -s ../pat-public/src/pat .
  • cd ..
  • scons -j4 --accelergy --static
  • cp build/timeloop-* ~/.local/bin
  • cd ../../..
  • git clone
  • accelergy
  • accelergyTables
  • python3 -m pip install git+
  • pip3 install jupyter
  • export PATH=$PATH:~/.local/bin
Now you can
  • cd timeloop-accelergy-exercises
  • jupyter notebook
  • go to workspace/exercises and pick the tutorial of your interest