vincentlv / dimmilitho Goto Github PK

Hi!

About two years ago, @google partnered with SkyWater to release a fully open source PDK for SkyWater's 130nm process technology (https://skywater-pdk.rtfd.io https://github.com/google/skywater-pdk). With silicon now starting to come back from the open source MPW program, there is a whole bunch of imaging happening which compares the generated GDS to the actual structures found in silicon. As well, I'm working on publishing publically imaging of the masks that were used to manufacture the open source MPW program. Lastly, Google released an optimized SRAM build space (https://github.com/google/skywater-pdk-libs-sky130_fd_bd_sram) which includes precalculated OPC.

As well, last week Google announced it has received funding to expand the program to include a 90nm process technology - https://opensource.googleblog.com/2022/07/SkyWater-and-Google-expand-open-source-program-to-new-90nm-technology.html

With all this, it would be awesome to have a fully open source OPC tooling that was compatible with these process technologies.
It would also be awesome to see examples in this repository targeting these real world, manufacturable processes.

hi,
I am experimenting with your package. It seems that maskxpitch/maskypitch in source and lens classes have a large impact on the final image. I noticed that by default those values are set as the xrange/yrange of the given mask. However, for the same mask, if I use different maskxptich and maskypitch, the calAI, calRI will create different arial and resist image. I wonder what is the meaning of maskxpitch and maskypitch and what is the correct way to set it if I need to simulate a large number of gds images with different sizes under the same condition?

thanks!

Mark

Hi,

I believe that your GDS parser uses a fixed scale of 0.001 (1000):

However, the NanGate library uses a scale of 0.0001 (10000). Therefore, the dimensions of the mask are off by 10x.

If you look at the contact width (layer 10) in the NOR2_X2.gds example, they should have a width of 65nm but instead, we see 650nm if you print out the polygon data.

Matt

hi,
I am the graduate student.I learned from your code.But I have some question about your code.Firstly,in the Source.py,why is (detax=wavelength/(NA*maskxpitch))?.Secondly,why did you use the Edeta function?Lastly,the zernike Coefficient（Cn）=0.0? I am very interested in computional lithography.I am looking forward to hearing from you.

thanks,
Yue