5 papers
AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization
Jiehao Wu, Zixiao Huang, Wenhao Li +3
Optimizing AscendC (Ascend C) operators for Ascend NPUs is difficult for two reasons. First, unlike CUDA, the ecosystem offers few public kernels to learn from. Second, performance…
UniGRPO: Unified Policy Optimization for Reasoning-Driven Visual Generation
Jie Liu, Zilyu Ye, Linxiao Yuan +8
Unified models capable of interleaved generation have emerged as a promising paradigm, with the community increasingly converging on autoregressive modeling for text and flow match…
Learning Virtual Machine Scheduling in Cloud Computing through Language Agents
JieHao Wu, Ziwei Wang, Junjie Sheng +3
In cloud services, virtual machine (VM) scheduling is a typical Online Dynamic Multidimensional Bin Packing (ODMBP) problem, characterized by large-scale complexity and fluctuating…
Scalable Reinforcement Learning for Virtual Machine Scheduling
Junjie Sheng, Jiehao Wu, Haochuan Cui +6
Recent advancements in reinforcement learning (RL) have shown promise for optimizing virtual machine scheduling (VMS) in small-scale clusters. The utilization of RL to large-scale…
SolSearch: An LLM-Driven Framework for Efficient SAT-Solving Code Generation
Junjie Sheng, Yanqiu Lin, Jiehao Wu +4
The Satisfiability (SAT) problem is a core challenge with significant applications in software engineering, including automated testing, configuration management, and program verif…