This is the recommened method for new users. Accelergy and Timeloop are avialable in the same docker.
git clone git@github.com:Accelergy-Project/accelergy.git
cd accelergy
pip3 install .
Accelergy communitcates with various energy/area estimation plug-ins to generate estimations for various technologies. We provide default plug-ins to get you started with estimating popular components in common architectures.
Responsible for generating large SRAM energy/area for various technology nodes and DRAM energy.
git clone https://github.com/HewlettPackard/cacti
cd cacti
make
cd ..
mv cacti ~/.local/bin/
git clone git@github.com:Accelergy-Project/accelergy-cacti-plug-in.git
cd accelergy-cacti-plug-in
pip3 install .
Responsible for generating the energy/area of various 45nm datapath components, e.g., intadder, intmultiplier, register files, etc.
git clone git@github.com:Accelergy-Project/accelergy-aladdin-plug-in.git
cd accelergy-aladdin-plug-in
pip3 install .
Allows easy integration of user-defined csv
table-based plug-ins. More detailes will be provided in plug-in API explanation.
git clone git@github.com:Accelergy-Project/accelergy-table-based-plug-ins.git
cd accelergy-table-based-plug-ins
pip3 install .
accelergyTables
~/.local/bin
, is appropriately added to $PATH accelergy
should be available in your python bin accelergy -h
shows the help message for the command