Intuitive Python API

PRGA is written in Python with an intuitive, modularized, and highly extensible API. Enjoy the smoothness of developing in a high-level programming language!


Templated File Generation

PRGA generates most files based on parameterized Jinja templates. Feel free to replace the templates without changing your Python code!

Learn more about Jinja

Open-Source CAD Tools

PRGA auto-generates scripts for implementing applications on your custom FPGA with open-source CAD tools, e.g. Yosys, VPR, etc.

Learn more about Yosys

Learn more about VPR

Customizable Architecture

PRGA features a highly customizable FPGA architecture at various levels. You are also welcome to bring your own designs or any third-party/proprietary IPs into your custom FPGAs!

ASIC-friendly RTL

PRGA-generated RTL is highly ASIC-friendly, both for implementation, characterization, and verification.

Incremental Verification

From behavioral simulation, to post-synthesis, LUT-based simulation, all the way to post-implementation simulation, PRGA features automated, incremental verification.

Princeton Reconfigurable Gate Array

Design, customize, and build your own FPGA!

  • Study FPGA architecture with accurate, gate-level timing, area and power characterization.
  • Research novel configuration protocol, e.g. partial reconfiguration, dynamic reconfiguration, multi-context FPGA, and secure bitstream!
  • Integrate an open-source embedded FPGA IP in your next SoC design!
  • And more…

Bring Your Own IPs into the Heterogeneous Architecture

This custom FPGA has an embedded hard PicoRV32 core (the large orange block in the middle), in addition to two types of CLBs (light and dark purple blocks), and some BRAM blocks (narrow cyan blocks). This figures shows the picosoc design implemented on this custom FPGA.

  • Figure generated by VPR

Try it youself

Multi-Modal Primitives

Increase the utilization rate of gates with multi-modal primitives.

  • LUT3 = 2 LUT2s with shared inputs
  • 8Kbit RAM can be used as 256x64b, 512x32b, 1024x16b, …
  • Also feel free to design your own multi-modal primitives!