Could Someone Give me Advice for Layer Mapping and DRC Script Optimization?

davidcook

Hello there,

I am new to KLayout and have been exploring its capabilities for layout editing and running custom DRC scripts. So far, I am impressed by how powerful the tool is, but I have come across a couple of challenges that I am hoping the community can help me with.

In my current project; I am working with multiple technologies. Managing the layer mapping across these technologies has become a bit cumbersome. I have been manually mapping layers in my .lyt file; but I am wondering if there is a more efficient way to handle layer mapping for multi-technology projects? Are there any best practices or scripts for automating this process?

My DRC scripts are functional but tend to run slowly on larger layouts. I suspect there are inefficiencies in how I am structuring my checks. For instance; I often repeat checks for overlapping shapes across multiple layers; and I am unsure how to consolidate these into fewer operations. Are there specific tips or examples of how to optimize DRC scripts for better performance?

Also, I have gone through this post; http://klayout.de/forum/discussion/1670/how-to-learn-to-write-the-drc-scripts-rpa which definitely helped me out a lot.

I have gone through the official documentation and a few examples; but I would love to hear how others are tackling these issues in real world workflows. If you could point me to any helpful resources; share example scripts; or suggest alternative approaches, that would be fantastic.

Thanks in advance for your help and assistance.

Matthias

Hi @davidcook,

I should write a book, I guess

I gave a talk once about optimization of DRC decks, specifically with respect to performance. Maybe that is helpful: https://wiki.f-si.org/index.php?title=Learning_from_GF180_PDK:_Best_practices_for_implementing_and_optimizing_KLayout_DRC_and_LVS_decks. There is also a video link and some links to related material. I think you should check this.

Amazingly, I find that ChatGPT is becoming an increasingly better source for advice. I guess, that is one of the advantages of Open Souce and a public community: AI will listen and learn from you

Regarding best practices, maybe you like to check the sources of some open PDKs, first of all the IHP PDK: https://github.com/IHP-GmbH/IHP-Open-PDK.

I don't have a specific recommendation, but I think a general advice maybe to generate files from common sources where possible.

For example, the GDS layer to name table is used in many places. So you can start with some CSV table and generate the .lyp file and the layer mapping part of .lyt, but also the input sections of DRC and LVS. Some files are XML, so you can use any kind of scripting framework for that purpose.

DRC and LVS are basically Ruby scripts and you can employ Ruby language features to automate tasks. So instead listing the input layers by adding "input" statements, you can scan some layer table - e.g. some CSV file - and execute the input statements inside the parser. All you need to know is that a layer is basically an object that you can pass around, stash in a hash or store inside your own classes. Ruby is quite powerful, but less prominent than Python today - but it still is widely used on MacOS and for Ruby on Rails for example.

It is not unrealistic to entirely execute a DRC from some configuration file - by scanning that file and reading rules from there inside some technology-agnostic DRC script. I don't have an example, and I'd only recommend that for simple width/space-alike DRC decks, but basically that should be possible.

Matthias