213 citations · 226 across the 6 of their papers we have counts for
6 papers
PRAGMA: A Profiling-Reasoned Multi-Agent Framework for Automatic Kernel Optimization
Kelun Lei, Hailong Yang, Huaitao Zhang +5
Designing high-performance kernels requires expert-level tuning and a deep understanding of hardware characteristics. Recent advances in large language models (LLMs) have enabled a…
LOw-cOst yet High-Performant Sparse Matrix-Matrix Multiplication on Arm SME Architectures
Kelun Lei, Hailong Yang, Kaige Zhang +8
Sparse matrix-dense matrix multiplication (SpMM) is a critical kernel in both scientific computing and emerging graph learning workloads. The recent Armv9 architecture introduces S…
Minions: Accelerating Large Language Model Inference with Aggregated Speculative Execution
Siqi Wang, Hailong Yang, Xuezhu Wang +10
Large language models (LLM) have recently attracted surging interest due to their outstanding capabilities across various domains. However, enabling efficient LLM inference is chal…
The Deep Learning Compiler: A Comprehensive Survey
Mingzhen Li, Yi Liu, Xiaoyan Liu +7
The difficulty of deploying various deep learning (DL) models on diverse DL hardware has boosted the research and development of DL compilers in the community. Several DL compilers…
Intelligent-Unrolling: Exploiting Regular Patterns in Irregular Applications
Changxi Liu, Hailong Yang, Xu Liu +2
Modern optimizing compilers are able to exploit memory access or computation patterns to generate vectorization codes. However, such patterns in irregular applications are unknown…
swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight
Jiarui Fang, Liandeng Li, Haohuan Fu +5
This paper reports our efforts on swCaffe, a highly efficient parallel framework for accelerating deep neural networks (DNNs) training on Sunway TaihuLight, the current fastest sup…