Want a faster ML processor? Do it yourself! -- A framework for playing with custom opcodes to accelerate TensorFlow Lite for Microcontrollers (TFLM). . . . . . Online tutorial: https://google.github.io/CFU-Playground/ For reference docs, see the link below.
Pin the Yosys package to a version compatible with the F4PGA Yosys plugins.
This fixes #808.
Tested: manually built the bitstream and tested it on an Arty 35T board with the CFU Playground firmware.
When the plugins package updates, we can unpin Yosys.
Also, comment out the download of the xc7a200t database to make the installation of F4PGA faster.
NOTE: After you sync to this update, you don't need to reinstall the entire Symbiflow/F4PGA environment. Just do this (while not inside the environment, at the root directory of the CFU-Playground repo):
# Update the existing Symbiflow F4PGA environment
make USE_SYMBIFLOW=1 env
Then enter the Symbiflow/F4PGA environment and use:
make enter-sf
cd proj/proj_template_v
make USE_SYMBIFLOW=1 bitstream
Pin the Yosys package to a version compatible with the F4PGA Yosys plugins.
This fixes #808.
Tested: manually built the bitstream and tested it on an Arty 35T board with the CFU Playground firmware.
When the plugins package updates, we can unpin Yosys.
Also, comment out the download of the xc7a200t database to make the installation of F4PGA faster.
NOTE: After you sync to this update, you don't need to reinstall the entire Symbiflow/F4PGA environment. Just do this (while not inside the environment, at the root directory of the CFU-Playground repo):
Then enter the Symbiflow/F4PGA environment and use: