3 papers
cs.AR2026
Sieve: Dynamic Expert-Aware PIM Acceleration for Evolving Mixture-of-Experts Models
Jungwoo Kim, Rubens Lacouture, Genghan Zhang +5
Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models (LLMs). However, the execution characteristics of MoE inference are changing rapidly a…
cs.PL2026
Streaming Tensor Programs: A Streaming Abstraction for Dynamic Parallelism
Gina Sohn, Genghan Zhang, Konstantin Hossfeld +5
Dynamic behaviors are becoming prevalent in tensor applications, like machine learning, where many widely used models contain data-dependent tensor shapes and control flow. However…
cs.AR2025
Hardware-based Heterogeneous Memory Management for Large Language Model Inference
Soojin Hwang, Jungwoo Kim, Sanghyeon Lee +2
A large language model (LLM) is one of the most important emerging machine learning applications nowadays. However, due to its huge model size and runtime increase of the memory fo…