12. Using FPGA AI Suite in Hostless DDR-Free Mode
To avoid use of external memory for storing graph weights and FPGA AI Suite IP configurations during inference, you can store these parameters within the IP using on-chip memory.
In this case, three types of memory initialization files (.mif) are required:
- ddrfree_filter_hw*.mif: Contains the graph filters.
- ddrfree_bias_scale_hw*.mif: Contains the graph biases and scaling factors.
- ddrfree_config.mif: Stores the FPGA AI Suite instructions for the compiled graph.
These files are generated using the dla_compiler tool that takes the architecture definition (.arch file) and the target neural network graph as inputs.
You must also enable input and output streaming when using DDR-free operation. The graph must have a large enough stream buffer depth to accommodate all of the intermediate results during inference.
The dla_build_example_design.py command can build design examples with DDR-free operation. The only streaming design example option currently supported is the agx7_iseries_ddrfree option. The design example created by this option targets the Agilex™ 7 FPGA I-Series Development Kit ES2 (DK-DEV-AGI027RBES).
To compile a bitstream with a DDR-free architecture, specify the directory that contains the DDR-free .mif files with the -–parameter_rom_dir option of the dla_build_example_design.py build command.
For details about creating the .mif file required for DDR-free operation, refer to Generating Artifacts for Hostless DDR-Free Operation
Section Content
Generating Artifacts for Hostless DDR-Free Operation
Hostless DDR-Free Design Example System Architecture
Hostless DDR-Free Design Example Quartus Prime System Console
Hostless DDR-Free Design Example JTAG to Avalon MM Host Register Map
Changing the ML Graph in a Hostless DDR-Free Architecture