6 papers
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…
Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
Joon Ha Kim, Geon-Woo Kim, Anoop Rachakonda +1
Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, since no single choice performs…
Reformulating KV Cache Eviction Problem for Long-Context LLM Inference
Tho Mai, Joo-Young Kim
Large language models (LLMs) support long-context inference but suffer from substantial memory and runtime overhead due to Key-Value (KV) Cache growth. Existing KV Cache eviction m…
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…
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…