activity
20222026
most citedDaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics

13 citations · 34 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Understanding and Exploiting Diagonal Attention Sparsity in Autoregressive Image Generation

Daeun Kim, Junwha Hong, Changhun Oh +3

Autoregressive image generation has emerged as a paradigm for multimodal AI systems due to its compatibility with transformer-based LLM serving infrastructures. However, generating…

cs.ET2026

Understanding the Performance Behaviors of End-to-End Protein Design Pipelines on GPUs

Jinwoo Hwang, Yeongmin Hwang, Tadiwos Meaza +2

Recent computational advances enable protein design pipelines to run end-to-end on GPUs, yet their heterogeneous computational behaviors remain undercharacterized at the system lev…

cs.AR2025

Neo: Real-Time On-Device 3D Gaussian Splatting with Reuse-and-Update Sorting Acceleration

Changhun Oh, Seongryong Oh, Jinwoo Hwang +3

3D Gaussian Splatting (3DGS) rendering in real-time on resource-constrained devices is essential for delivering immersive augmented and virtual reality (AR/VR) experiences. However…

cs.AR2025★ 6 cited

Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Serving

Wonung Kim, Yubin Lee, Yoonsung Kim +8

Transformers are the driving force behind today's Large Language Models (LLMs), serving as the foundation for their performance and versatility. Yet, their compute and memory costs…

cs.DC2025

Déjà Vu: Efficient Video-Language Query Engine with Learning-based Inter-Frame Computation Reuse

Jinwoo Hwang, Daeun Kim, Sangyeop Lee +8

Recently, Video-Language Models (VideoLMs) have demonstrated remarkable capabilities, offering significant potential for flexible and powerful video query systems. These models typ…

cs.AR2025★ 1 cited

MixDiT: Accelerating Image Diffusion Transformer Inference with Mixed-Precision MX Quantization

Daeun Kim, Jinwoo Hwang, Changhun Oh +1

Diffusion Transformer (DiT) has driven significant progress in image generation tasks. However, DiT inferencing is notoriously compute-intensive and incurs long latency even on dat…

cs.LG2024★ 10 cited

Accelerating String-Key Learned Index Structures via Memoization-based Incremental Training

Minsu Kim, Jinwoo Hwang, Guseul Heo +3

Learned indexes use machine learning models to learn the mappings between keys and their corresponding positions in key-value indexes. These indexes use the mapping information as…

cs.AR2024★ 13 cited

DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics

Yoonsung Kim, Changhun Oh, Jinwoo Hwang +6

Deep neural network (DNN) video analytics is crucial for autonomous systems such as self-driving vehicles, unmanned aerial vehicles (UAVs), and security robots. However, real-world…

cs.CV2022★ 4 cited

CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics

Jinwoo Hwang, Minsu Kim, Daeun Kim +5

Modern retrospective analytics systems leverage cascade architecture to mitigate bottleneck for computing deep neural networks (DNNs). However, the existing cascades suffer two lim…