4 papers
CUDABench: Benchmarking LLMs for Text-to-CUDA Generation
Jiace Zhu, Wentao Chen, Qi Fan +6
Recent studies have demonstrated the potential of Large Language Models (LLMs) in generating GPU Kernels. Current benchmarks focus on the translation of high-level languages into C…
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…
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-…
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…