4 papers
GCL-Sampler: Discovering Kernel Similarity for Sampled GPU Simulation via Graph Contrastive Learning
Jiaqi Wang, Jingwei Sun, Jiyu Luo +2
GPU architectural simulation is orders of magnitude slower than native execution, necessitating workload sampling for practical speedups. Existing methods rely on hand-crafted feat…
RSH-SpMM: A Row-Structured Hybrid Kernel for Sparse Matrix-Matrix Multiplication on GPUs
Aiying Li, Jingwei Sun, Han Li +2
Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental computation in graph analytics, scientific simulation, and sparse deep learning workloads. However, the extreme irregula…
Token Pruning for In-Context Generation in Diffusion Transformers
Junqing Lin, Xingyu Zheng, Pei Cheng +3
In-context generation significantly enhances Diffusion Transformers (DiTs) by enabling controllable image-to-image generation through reference examples. However, the resulting inp…
Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage
Junqing Lin, Jingwei Sun, Mingge Lu +1
Sparse Matrix-Vector Multiplication (SpMV) has become a critical performance bottleneck in the local deployment of sparse Large Language Models (LLMs), where inference predominantl…