40 citations · 40 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 40 cited
Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching
Yeonhong Park, Sunhong Min, Jae W. Lee
Recently, Graph Neural Networks (GNNs) have been receiving a spotlight as a powerful tool that can effectively serve various inference tasks on graph structured data. As the size o…
cs.CV2022
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training
Jonghyun Bae, Woohyeon Baek, Tae Jun Ham +1
The training process of deep neural networks (DNNs) is usually pipelined with stages for data preparation on CPUs followed by gradient computation on accelerators like GPUs. In an…
cs.CR2021
Mithril: Cooperative Row Hammer Protection on Commodity DRAM Leveraging Managed Refresh
Michael Jaemin Kim, Jaehyun Park, Yeonhong Park +5
Since its public introduction in the mid-2010s, the Row Hammer (RH) phenomenon has drawn significant attention from the research community due to its security implications. Althoug…