16 citations · 22 across the 9 of their papers we have counts for
5 papers · 1 filter
NOVA: Technology-Architecture Co-Design of Near-Memory Processing for Attention-SSM-MoE Hybrid LLM Inference
In-Jun Jung, Jaeha Min, Joo-Young Kim
The rapid evolution of hybrid large language models (LLMs), which interleave grouped-query-attention (GQA), state-space model (SSM), and Mixture-of-Experts (MoE) layers, introduces…
3DLS: A 3D Logic-Stacked Architecture for Disaggregated LLM Serving
Jaehun Lee, In-Jun Jung, Joo-Young Kim
Large language model (LLM) serving increasingly combines prefill-decode (PD) disaggregation with tensor parallelism (TP) to support large models and long contexts. In conventional…
LightNobel: Improving Sequence Length Limitation in Protein Structure Prediction Model via Adaptive Activation Quantization
Seunghee Han, Soongyu Choi, Joo-Young Kim
Recent advances in Protein Structure Prediction Models (PPMs), such as AlphaFold2 and ESMFold, have revolutionized computational biology by achieving unprecedented accuracy in pred…
SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models
Jinho Yang, Ji-Hoon Kim, Joo-Young Kim
Deep Learning Recommendation Models (DLRMs) play a crucial role in delivering personalized content across web applications such as social networking and video streaming. However, w…
Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization
Minsu Kim, Seongmin Hong, RyeoWook Ko +5
Modern Large Language Model serving system batches multiple requests to achieve high throughput, while batching attention operations is challenging, rendering memory bandwidth a cr…