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cs.CL2025
TimeBill: Time-Budgeted Inference for Large Language Models
Qi Fan, An Zou, Yehan Ma
Large Language Models (LLMs) are increasingly deployed in time-critical systems, such as robotics, autonomous driving, embodied intelligence, and industrial automation, where gener…
cs.LG2025
CUDA-LLM: LLMs Can Write Efficient CUDA Kernels
Wentao Chen, Jiace Zhu, Qi Fan +2
Large Language Models (LLMs) have demonstrated strong capabilities in general-purpose code generation. However, generating the code which is deeply hardware-specific, architecture-…
cs.DC2025
A Survey of Real-time Scheduling on Accelerator-based Heterogeneous Architecture for Time Critical Applications
An Zou, Yuankai Xu, Yinchen Ni +6
Accelerator-based heterogeneous architectures, such as CPU-GPU, CPU-TPU, and CPU-FPGA systems, are widely adopted to support the popular artificial intelligence (AI) algorithms tha…