2 papers
cs.DC2025
GPU Kernel Optimization Beyond Full Builds: An LLM Framework with Minimal Executable Programs
Ruifan Chu, Anbang Wang, Xiuxiu Bai +2
In high-performance computing, hotspot GPU kernels are primary bottlenecks, and expert manual tuning is costly and hard to port. Large language model methods often assume kernels c…
cs.LG2025
GradES: Significantly Faster Training in Transformers with Gradient-Based Early Stopping
Qifu Wen, Xi Zeng, Zihan Zhou +4
Early stopping monitors global validation loss and halts all parameter updates simultaneously, which is computationally costly for large transformers due to the extended time requi…