activity
20232026
most citedHongTu: Scalable Full-Graph GNN Training on Multiple GPUs (via communication-optimized CPU data offloading)

23 citations · 34 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.AR2026

Co-Designing Graph-based Approximate Nearest Neighbor Search at Billion Scale for Processing-in-Memory

Sitian Chen, Yusen Li, Yao Chen +3

Approximate Nearest Neighbor Search (ANNS) is a core primitive in modern AI systems, and graph-based methods currently offer the best accuracy-efficiency trade-off at scale. The wo…

cs.AR2026

XtraMAC: An Efficient MAC Architecture for Mixed-Precision LLM Inference on FPGA

Feng Yu, Hongshi Tan, Yao Chen +2

The widespread adoption of mixed-precision quantization in large language models (LLMs) has created demand for hardware that can efficiently perform multiply-accumulate (MAC) opera…

cs.AR2026

RidgeWalker: Perfectly Pipelined Graph Random Walks on FPGAs

Hongshi Tan, Yao Chen, Xinyu Chen +4

Graph Random Walks (GRWs) offer efficient approximations of key graph properties and have been widely adopted in many applications. However, GRW workloads are notoriously difficult…

cs.AR2025

HLStrans: Dataset for C-to-HLS Hardware Code Synthesis

Qingyun Zou, Nuo Chen, Yao Chen +2

High-Level Synthesis (HLS) enables hardware design from C/C++ kernels but requires extensive transformations, such as restructuring code, inserting pragmas, adapting data types, an…

cs.AR2023★ 9 cited

LightRW: FPGA Accelerated Graph Dynamic Random Walks

Hongshi Tan, Xinyu Chen, Yao Chen +2

Graph dynamic random walks (GDRWs) have recently emerged as a powerful paradigm for graph analytics and learning applications, including graph embedding and graph neural networks.…