2 papers
cs.DC2026
LLM-Based Porting of Optimized C++ to CUDA Through Deoptimization and Reoptimization
Daichi Mukunoki, Ryo Mikasa, Shunichiro Hayashi +2
When porting high-performance computing (HPC) code from CPU to GPU, CPU-oriented optimizations may obstruct LLM-based CUDA translation. We design and evaluate a Deopt-Reopt workflo…
cs.LG2026
Improving HPC Code Generation Capability of LLMs via Online Reinforcement Learning with Real-Machine Benchmark Rewards
Ryo Mikasa, Shun-ichiro Hayashi, Daichi Mukunoki +2
Large language models (LLMs) have demonstrated strong code generation capabilities, yet the runtime performance of generated code is not guaranteed, and there have been few attempt…