1 code implementation • 11 Mar 2024 • Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee
Our work, Smart-Infinity, addresses the storage bandwidth bottleneck of storage-offloaded LLM training using near-storage processing devices on a real system.
1 code implementation • 11 Mar 2024 • Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee
In this situation, adversarial distillation is a promising option which aims to distill the robustness of the teacher network to improve the robustness of a small student network.
no code implementations • 12 Nov 2023 • Jaeyong Song, Hongsun Jang, Jaewon Jung, Youngsok Kim, Jinho Lee
According to the growth in the dataset and the model size used for GNNs, an important problem is that it becomes nearly impossible to keep the whole network on GPU memory.
1 code implementation • 29 Jan 2023 • Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee
However, this results in a high overhead of redundant teacher execution, low GPU utilization, and extra data loading.
no code implementations • 24 Jan 2023 • Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee
Compressing the communication is one way to mitigate the overhead by reducing the inter-node traffic volume; however, the existing compression techniques have critical limitations to be applied for NLP models with 3D parallelism in that 1) only the data parallelism traffic is targeted, and 2) the existing compression schemes already harm the model quality too much.
1 code implementation • 16 Apr 2019 • Jaewon Jung, Jongyoul Park
Visual relationship detection is an intermediate image understanding task that detects two objects and classifies a predicate that explains the relationship between two objects in an image.