2 papers
cs.LG2024
MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models
Taehyun Kim, Kwanseok Choi, Youngmock Cho +3
Mixture-of-Experts (MoE) large language models (LLM) have memory requirements that often exceed the GPU memory capacity, requiring costly parameter movement from secondary memories…
cs.CV2024
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator
Wonhyeok Choi, Mingyu Shin, Hyukzae Lee +3
Real-time processing is crucial in autonomous driving systems due to the imperative of instantaneous decision-making and rapid response. In real-world scenarios, autonomous vehicle…