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cs.AR2025
Designing Spatial Architectures for Sparse Attention: STAR Accelerator via Cross-Stage Tiling
Huizheng Wang, Taiquan Wei, Hongbin Wang +6
Large language models (LLMs) rely on self-attention for contextual understanding, demanding high-throughput inference and large-scale token parallelism (LTPP). Existing dynamic spa…
cs.AI2025
cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution
Jinwu Chen, Qidie Wu, Bin Li +5
Optimizing CUDA kernels is a challenging and labor-intensive task, given the need for hardware-software co-design expertise and the proprietary nature of high-performance kernel li…
cs.DC2025
HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration
Jiaqi Lv, Xufeng He, Yanchen Liu +7
The rapid growth of deep learning has driven exponential increases in model parameters and computational demands. NVIDIA GPUs and their CUDA-based software ecosystem provide robust…