Sungmin Yun
I am a Senior Deep Learning Performance Architect at NVIDIA, focusing on AI acceleration, performance analysis, and optimization. My work aims to maximize the performance and efficiency of AI systems through hardware–software co-design.
My experience spans accelerator design, hardware profiling, performance modeling, and kernel programming for modern AI architectures, including MoE, MLA, RAG, and diffusion. My research has focused on efficient LLM serving, Multi-LoRA inference, and RAG pipelines. I also developed LLMSimulator, an open-source end-to-end LLM performance simulator.
Previously, I was a postdoctoral researcher at Seoul National University (SNU). I received my Ph.D. in Artificial Intelligence from SNU, under the supervision of Prof. Jung Ho Ahn in the SCALE Lab. I received my B.S. in Integrated Information Technology from Yonsei University in 2020.
Publications
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Clone: A Collaborative Multi-device System for Retrieval-Augmented Generation over CXL
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Rethinking LLM Inference Bottlenecks: Insights from Latent Attention and Mixture-of-Experts
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SSD Offloading for LLM Mixture-of-Experts Weights Considered Harmful in Energy Efficiency
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COSMOS: A CXL-Based Full In-Memory System for Approximate Nearest Neighbor Search
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Anaheim: Architecture and Algorithms for Processing Fully Homomorphic Encryption in Memory
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Duplex: A Device for Large Language Models with Mixture of Experts, Grouped Query Attention, and Continuous Batching
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CLAY: CXL-based Scalable NDP Architecture Accelerating Embedding Layers
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GraNDe: Efficient Near-Data Processing Architecture for Graph Neural Networks
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GraNDe: Near-Data Processing Architecture with Adaptive Matrix Mapping for Graph Convolutional Networks
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TRiM: Enhancing Processor-Memory Interfaces with Scalable Tensor Reduction in Memory
Education
Experience
Deep learning application performance analysis.
Led research on LLM serving systems, Multi-LoRA inference, and RAG pipeline acceleration.
Awards
Invited Presentations
Academic Service
Program Committee
- ISCA 2026 — Lightweight Program Committee Member
Journal Review
- IEEE Transactions on Computers
- IEEE Transactions on Circuits and Systems for Artificial Intelligence
- IEEE Computer Architecture Letters
- Future Generation Computer Systems
- Journal of Supercomputing