3 citations · 5 across the 4 of their papers we have counts for
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cs.DC2025★ 1 cited
FpgaHub: Fpga-centric Hyper-heterogeneous Computing Platform for Big Data Analytics
Zeke Wang, Jie Zhang, Hongjing Huang +10
Modern data analytics requires a huge amount of computing power and processes a massive amount of data. At the same time, the underlying computing platform is becoming much more he…
cs.DC2024
DisDP: Disaggregating Compute, Network, and Storage for Model-Sharded Data-Parallel Training
Mo Sun, Zihan Yang, Changyue Liao +5
Model-sharded data parallelism (MSDP), e.g., ZeRO, evenly shards the model states across all GPUs, and thus has been widely adopted by LLM pre-training, such as Llama and DeepSeek,…
cs.DC2023★ 3 cited
Helios: An Efficient Out-of-core GNN Training System on Terabyte-scale Graphs with In-memory Performance
Jie Sun, Mo Sun, Zheng Zhang +6
Training graph neural networks (GNNs) on large-scale graph data holds immense promise for numerous real-world applications but remains a great challenge. Several disk-based GNN sys…