AI as a Compiler: Compiling Triton kernels without the Triton compiler
We investigate whether large language models can replace the conventional optimizing and lowering pipeline, a process that we call AI lowering. We study AI lowering from Triton to NVIDIA PTX: an LLM agent translates Triton kernels directly into PTX. We build an environment that evaluates candidate PTX, and an agentic harness in which an LLM translates Triton kernels into PTX.
- ▪We investigate whether large language models can replace the conventional optimizing and lowering pipeline, a process that we call AI lowering.
- ▪We study AI lowering from Triton to NVIDIA PTX: an LLM agent translates Triton kernels directly into PTX.
- ▪We build an environment that evaluates candidate PTX, and an agentic harness in which an LLM translates Triton kernels into PTX.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2609.36800 |
| Publication time | Wed, 30 Sep 2026 23:01:35 +0000 |
| Retrieval time | 2026-09-30T23:07:05.717Z |
| Last seen | 2026-09-30T23:07:05.717Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | nySVXI7tY8tA · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2609.36800 (cs) [Submitted on 29 Sep 2026] Title:AI as a Compiler: Compiling Triton kernels without the Triton compiler Authors:François Costa, Charly Castes, Thomas Bourgeat, Azalia Mirhoseini View a PDF of the paper titled AI as a Compiler: Compiling Triton kernels without the Triton compiler, by Fran\c{c}ois Costa and 3 other authors View PDF HTML (experimental) Abstract:Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language models can replace the conventional optimizing and lowering pipeline, a process that we call AI lowering. We study AI lowering from Triton to NVIDIA PTX: an LLM agent translates Triton kernels directly into PTX.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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