16 citations · 22 across the 9 of their papers we have counts for
4 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…
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…