{"slug": "zgc-tensor-graphs-numerical-computation-compiler", "title": "ZGC: Tensor Graphs/Numerical computation compiler", "summary": "Developer krypticlogan released ZGC, a tensor graph compiler written in Zig, on GitHub after pivoting from a specialized neural network graph runtime. ZGC targets Zig versions 0.16.0 with 0.17.0 support planned, and the developer reports hitting the compiler's eval branch quota as compile-time work grows. LLMs assisted with problem-space exploration, architectural ideas, refactors, validation and testing, while the developer made all final implementation decisions and reviewed any LLM-generated code.", "body_md": "Started as a specialized runtime for neural network graphs, and pivoted to a tensor graph compiler, but really they’re the same thing?\n\n[https://github.com/krypticlogan/zig-graph-compiler](https://github.com/krypticlogan/zig-graph-compiler)\n\nAround February/March I got curious about zig comptime and how I could use it effectively. I figured I would use it to truly specialize a particular program, and the forward step for a neural network graph was a good task. I got it to work, but in my quest for optimization, I realized it might be better to just have an underlying tensor computation system that can specialize itself. That’s how I wound up with ZGC, and it’s reached a stage that I would like to share and gather feedback. Though it was a bit of a new domain for me, it felt like comptime made implementations easy to reason about and I’ve had a lot of fun working on it.\n\nOne problem that I’ve begun to run into as the compiler (and compile-time work) grows is the eval branch quota. It’s simple enough to scale, but it also becomes user-facing at times. I’m not sure how this is properly dealt with, or more likely, is intentional design that I shouldn’t try to avoid?\n\n0.16.0, 0.17.0 soon\n\nLLMs assisted in problem-space exploration, architectural ideas/concerns, refactors, validation, and testing.\n\nFinal implementation decisions were made by me, the developer, and any LLM-generated code was reviewed and edited by me.", "url": "https://wpnews.pro/news/zgc-tensor-graphs-numerical-computation-compiler", "canonical_source": "https://ziggit.dev/t/zgc-tensor-graphs-numerical-computation-compiler/17866#post_1", "published_at": "2026-10-06 07:15:48+00:00", "updated_at": "2026-10-06 07:19:03.514353+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "neural-networks", "developer-tools", "ai-infrastructure"], "entities": ["ZGC", "Zig", "krypticlogan", "GitHub"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/zgc-tensor-graphs-numerical-computation-compiler", "markdown": "https://wpnews.pro/news/zgc-tensor-graphs-numerical-computation-compiler.md", "text": "https://wpnews.pro/news/zgc-tensor-graphs-numerical-computation-compiler.txt", "jsonld": "https://wpnews.pro/news/zgc-tensor-graphs-numerical-computation-compiler.jsonld"}}