# XUANTIE-RV/wujian100_open

IC design and development should be faster，simpler and more reliable

Repository: https://github.com/XUANTIE-RV/wujian100_open
Canonical: https://ross.abutalabs.com/products/wujian100_open
Language: Verilog
License: MIT
License Family: permissive
Last push: 2021-12-31T09:23:38+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2510, "days_push": 1706, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2013, forks 598 (observed 2026-08-28T04:06:05.235611+00:00)

## What it is
wujian100_open is an open-source RISC-V-based MCU SoC platform from T-Head, providing RTL source code, an SDK, simulation scripts, and FPGA emulation support. It enables developers to simulate with EDA tools like iverilog/VCS, generate FPGA bitstreams, and build an open MCU ecosystem.

## Use cases
- simulate an open-source RISC-V SoC with iverilog or VCS
- emulate an MCU SoC on an FPGA board
- develop and test custom IP cores on a reference SoC
- learn SoC design from complete RTL source code
- build embedded software with the RISC-V toolchain and SDK

## When to choose
- you want a fully open MCU SoC for learning or prototyping
- you need a reference RISC-V platform for FPGA emulation
- you want to develop or verify custom SoC IP blocks

## When to avoid
- you need a production-grade, commercially supported MCU
- you require active maintenance or recent updates
- you need a high-performance application processor rather than an MCU

## Facets
- artifact type: application
- maturity: maintenance
- function: simulation, embedded, sdk, testing
- domain: hardware, embedded-systems, developer-tools
- platform: cli
- tags: risc-v, soc, fpga, verilog, mcu, open-source-hardware, eda, linux

## Member repositories
- XUANTIE-RV/wujian100_open (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:05.235611+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:00:51.800396+00:00, confidence not recorded.
  - readme: https://github.com/XUANTIE-RV/wujian100_open (fetched 2026-08-28T04:06:05.235611+00:00, sha 03eddb764cbb)
- Data as of 2026-08-30T08:39:29.467469+00:00.