Are there any plans to support the GW1NSR-4C chips with hard Cortex-M3 core?

[skyandray]

How to use apicula on GW1NSR-4C chip with or without Cortex-M3 support?

[pepijndevos]

I assume this is for the Tang Nano 4K? Well there are plans, but there is work to be done. According to the product page this device requires IDE version v1.9.7.01 while Apicula is currently using v1.9.3.01 and the two have a completely incompatible TCL API.

Generally it's quite easy to add support for a new device, especially since we already support GW1N-4 and GW1NS-2C, but the main blocker is upgrading the IDE version that's used for fuzzing.

If you're willing to get your hands dirty, this is the main thing that needs changing: https://github.com/YosysHQ/apicula/blob/4140d04ce3d1ebebbbf1fe84a59be57af1a73219/apycula/tiled_fuzzer.py#L393

Beyond that, it's possible small changes are needed to the _h4x.py files that parse vendor data files, in case any changes happened there.

And then a bunch of testing. Hopefully everything just keeps working, but if there are any deep changes into how PnR works then ho boy that's going to be a lot of nasty debugging.

[uis246]

I would ask "Any news?", but it's only 13 days old. I hope chip support will be added. What about hard core?

[pepijndevos]

https://github.com/YosysHQ/apicula/pull/55

[uis246]

GW1NS-2C has hardcore. Is it supported only in newer version?

[pepijndevos]

Apicula does not support hard core yet. Contributions welcome

[pepijndevos]

71

[uis246]

Yeah, thank you