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20232026
most citedX-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

2 citations · 3 across the 9 of their papers we have counts for

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cs.AR2025

CuAsmRL: Optimizing GPU SASS Schedules via Deep Reinforcement Learning

Guoliang He, Eiko Yoneki

Large language models (LLMs) are remarked by their substantial computational requirements. To mitigate the cost, researchers develop specialized CUDA kernels, which often fuse seve…

cs.AR2024

SIP: Autotuning GPU Native Schedules via Stochastic Instruction Perturbation

Guoliang He, Eiko Yoneki

Large language models (LLMs) have become a significant workload since their appearance. However, they are also computationally expensive as they have billions of parameters and are…