9 citations · 14 across the 10 of their papers we have counts for
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cs.DC2026
Hardware-accelerated Aggregation: Unification and Specialization
Alireza Shateri, Hongshi Tan, Michael Ng +2
The high efficiency of domain-specific hardware has sparked substantial interest in adopting accelerators in data analytics systems. Among many choices, GPUs and FPGAs thrived as t…
cs.DC2021★ 3 cited
ThundeRiNG: Generating Multiple Independent Random Number Sequences on FPGAs
Hongshi Tan, Xinyu Chen, Yao Chen +2
In this paper, we propose ThundeRiNG, a resource-efficient and high-throughput system for generating multiple independent sequences of random numbers (MISRN) on FPGAs. Generating M…
cs.DC2020
HaoCL: Harnessing Large-scale Heterogeneous Processors Made Easy
Yao Chen, Xin Long, Jiong He +5
The pervasive adoption of Deep Learning (DL) and Graph Processing (GP) makes it a de facto requirement to build large-scale clusters of heterogeneous accelerators including GPUs an…