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

23 citations · 42 across the 9 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

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench

Qingyun Zou, Feng Yu, Hongshi Tan +2

We ask whether agentic AI systems built for software engineering transfer to realistic hardware engineering. Existing hardware LLM benchmarks isolate sub-tasks but none jointly req…

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.AR2024

NOVA: NoC-based Vector Unit for Mapping Attention Layers on a CNN Accelerator

Mohit Upadhyay, Rohan Juneja, Weng-Fai Wong +1

Attention mechanisms are becoming increasingly popular, being used in neural network models in multiple domains such as natural language processing (NLP) and vision applications, e…

cs.AR2024★ 6 cited

Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic

Daniel Gerlinghoff, Benjamin Chen Ming Choong, Rick Siow Mong Goh +2

Recent advancements in neural network quantisation have yielded remarkable outcomes, with three-bit networks reaching state-of-the-art full-precision accuracy in complex tasks. The…