@AnnmariaKAntony: LLMs are good at CUDA because the internet is full of it. But a model that gives you highly optimized CUDA may still st…

X AI KOLs Timeline 07/02/26, 09:38 PM Models

open-source cuda hip amd gpu training synthetic-data

Summary

A multi-agent synthetic data pipeline with SFT and GRPO RL post-training improves HIP compilation and correctness on AMD MI350X GPUs for a 14B open-source model.

LLMs are good at CUDA because the internet is full of it. But a model that gives you highly optimized CUDA may still struggle to write compilable HIP. We built a synthetic data pipeline with multi-agent search and post-trained a 14B open-source model with SFT + GRPO RL, leading to substantially better HIP compilation + correctness rates on AMD MI350X GPUs.

Original Article

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Cached at: 07/03/26, 10:42 PM

LLMs are good at CUDA because the internet is full of it. But a model that gives you highly optimized CUDA may still struggle to write compilable HIP.

We built a synthetic data pipeline with multi-agent search and post-trained a 14B open-source model with SFT + GRPO RL, leading to substantially better HIP compilation + correctness rates on AMD MI350X GPUs.

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