87 citations · 95 across the 7 of their papers we have counts for
7 papers
HA-RAG: Hotness-Aware RAG Acceleration via Mixed Precision and Data Placement
Danying Ge, Jianhua Gao, Yixue Yang +1
Retrieval-Augmented Generation (RAG) improves model output accuracy by leveraging external knowledge bases, serving as an effective solution to address hallucination issues and kno…
From Profiling to Optimization: Unveiling the Profile Guided Optimization
Bingxin Liu, Yinghui Huang, Jianhua Gao +4
Profile Guided Optimization (PGO) uses runtime profiling to direct compiler optimization decisions, effectively combining static analysis with actual execution behavior to enhance…
Automatic Task Detection and Heterogeneous LLM Speculative Decoding
Danying Ge, Jianhua Gao, Qizhi Jiang +2
Speculative decoding, which combines a draft model with a target model, has emerged as an effective approach to accelerate large language model (LLM) inference. However, existing m…
Cascaded Prediction and Asynchronous Execution of Iterative Algorithms on Heterogeneous Platforms
Jianhua Gao, Bingjie Liu, Yizhuo Wang +2
Owing to the diverse scales and varying distributions of sparse matrices arising from practical problems, a multitude of choices are present in the design and implementation of spa…
Precision-Aware Iterative Algorithms Based on Group-Shared Exponents of Floating-Point Numbers
Jianhua Gao, Jiayuan Shen, Yuxiang Zhang +2
Iterative solvers are frequently used in scientific applications and engineering computations. However, the memory-bound Sparse Matrix-Vector (SpMV) kernel computation hinders the…
A Systematic Literature Survey of Sparse Matrix-Vector Multiplication
Jianhua Gao, Bingjie Liu, Weixing Ji +1
Sparse matrix-vector multiplication (SpMV) is a crucial computing kernel with widespread applications in iterative algorithms. Over the past decades, research on SpMV optimization…
A Systematic Survey of General Sparse Matrix-Matrix Multiplication
Jianhua Gao, Weixing Ji, Fangli Chang +4
General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from researchers in graph analyzing, scientific computing, and deep learning. Many optimization te…