Papers
Topics
Authors
Recent
2000 character limit reached

Agentic Operator Generation for ML ASICs (2512.10977v1)

Published 3 Dec 2025 in cs.DC, cs.AR, and cs.PL

Abstract: We present TritorX, an agentic AI system designed to generate functionally correct Triton PyTorch ATen kernels at scale for emerging accelerator platforms. TritorX integrates open-source LLMs with a custom linter, JIT compilation, and a PyTorch OpInfo-based test harness. This pipeline is compatible with both real Meta Training and Inference Accelerator (MTIA) silicon and in hardware simulation environments for next-generation devices. In contrast to previous kernel-generation approaches that prioritize performance for a limited set of high-usage kernels, TritorX prioritizes coverage. Our system emphasizes correctness and generality across the entire operator set, including diverse data types, shapes, and argument patterns. In our experiments, TritorX successfully generated kernels and wrappers for 481 unique ATen operators that pass all corresponding PyTorch OpInfo tests (over 20,000 in total). TritorX paves the way for overnight generation of complete PyTorch ATen backends for new accelerator platforms.

Summary

We haven't generated a summary for this paper yet.

Whiteboard

Paper to Video (Beta)

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.