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20212026
most citedHongTu: Scalable Full-Graph GNN Training on Multiple GPUs (via communication-optimized CPU data offloading)

23 citations · 41 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.AR2026

ECO: Energy-Oriented Configuration Optimization for Attention FFN Disaggregated LLM Serving

Zou Qingyun, Bin Gao, Zhuobin Huang +3

Energy-efficient LLM serving requires minimizing serving GPU energy while meeting latency and throughput service-level objectives (SLOs). Attention--FFN disaggregation (AFD) enable…

cs.AR2026

Reward-Weighted On-Policy Distillation with an Open Property-Equivalence Verifier for NL-to-SVA Generation

Qingyun Zou, Yingze Li, Tianen Liu +2

LLM-based generation of SystemVerilog Assertions (SVA) is often reported as nearing saturation, with the strongest specialized model reaching accuracy on NL2SVA-Human.…

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.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.…

cs.AR2022★ 1 cited

ReGraph: Scaling Graph Processing on HBM-enabled FPGAs with Heterogeneous Pipelines

Xinyu Chen, Yao Chen, Feng Cheng +3

The use of FPGAs for efficient graph processing has attracted significant interest. Recent memory subsystem upgrades including the introduction of HBM in FPGAs promise to further a…