17 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.DC2026
KernelBrain: Coarse-to-Fine, Budget-Aware Search for Agentic GPU Kernel Optimization
Shuai Che, Gang Peng
Automating GPU kernel optimization remains difficult in practice: generated variants can violate correctness constraints, runtime measurements are noisy, and search often stalls ea…
cs.DC2019★ 17 cited
Software-defined Design Space Exploration for an Efficient DNN Accelerator Architecture
Ye Yu, Yingmin Li, Shuai Che +2
Deep neural networks (DNNs) have been shown to outperform conventional machine learning algorithms across a wide range of applications, e.g., image recognition, object detection, r…
cs.NE2019★ 8 cited
Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM
Hongxu Yin, Guoyang Chen, Yingmin Li +3
Many long short-term memory (LSTM) applications need fast yet compact models. Neural network compression approaches, such as the grow-and-prune paradigm, have proved to be promisin…