ASCII
Architectures, Systems, and Computing for Intelligence Innovations
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ASCII lab explores the future of intelligent computing across architectures, systems, and applications. We design processors and system architectures that perform computing efficiently. Our lab also creates methods that allow AI to work in real-world environments like embedded systems, even with limited resources. By combining hardware and software innovation, we aim to build intelligent systems that are both practical and powerful.
Recruiting Researchers
Recruiting Researchers
Undergraduate interns & Graduate students are welcome.
Please send your inquiries to hjkal@ajou.ac.kr
NEWS
NEWS
Nov. 29, 2025 Dr. Kal presents a tutorial session titled ‘Embodied AI Computing in Embedded Systems’ at the Autumn Annual Conference of the IEIE
Sep. 1, 2025 ASCII Lab Opens Its Doors
Research Interests
Research Interests
Computer Architectures
Computer Architectures
We cover CPU, GPU, accelerators, and memory architecture. Our work explores these components for future computing demands.
Embedded Systems
Embedded Systems
This research involves software acceleration on embedded boards, with a focus on developing AI or robotics frameworks
Intelligence Computing
Intelligence Computing
We develop system software based on a deep understanding of applications, bridging the gap between hardware and intelligent systems.
Selected Publications
Selected Publications
ISCA'25
TOP-TIER Jaewon Kwon, Yongju Lee, Jiwan Kim, Enhyeok Jang, Hongju Kal, and Won Woo Ro, "Garibaldi: A Pairwise Instruction-Data Management Scheme for Enhancing Shared Last-Level Cache Performance in Server Workloads" (LINK)
JSA'24
SCI Q1 Gun Ko, Jiwon Lee, Hongju Kal, Hyunwuk Lee, and Won Woo Ro, "REC: Enhancing fine-grained cache coherence protocol in multi-GPU systems" (LINK)
MICRO'23
TOP-TIER Hongju Kal, Chanyoung Yoo, and Won Woo Ro, "AESPA: Asynchronous Execution Scheme to Exploit Bank-Level Parallelism of Processing-in-Memory" (LINK)
MICRO'23
TOP-TIER Jaewon Kwon, Yongju Lee, Hongju Kal, Minjae Kim, Youngsok Kim, and Won Woo Ro, "McCore: A Holistic Management of High-Performance Heterogeneous Multicores" (LINK)
JSA'23
SCI Q1 Hongju Kal, Hyoseong Choi, Ipoom Jeong, Joon-Sung Yang, and Won Woo Ro, "A Convertible Neural Processor Supporting Adaptive Quantization for Real-Time Neural Networks" (LINK)
ISCA'21
TOP-TIER Hongju Kal, Seokmin Lee, Gun Ko, and Won Woo Ro, "SPACE: Locality-Aware Processing in Heterogeneous Memory for Personalized Recommendations" (LINK)
Access'21
SCI Q2 Won Jeon, Jiwon Lee, Dongseok Kang, Hongju Kal, and Won Woo Ro, "PIMCaffe: Functional Evaluation of a Machine Learning Framework for In-Memory Neural Processing Unit" (LINK)
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