Disintegrated control for energy-efficient and heterogeneous memory systems. - Tae Jun Ham; Bharath K. Chelepalli; Neng Xue; Benjamin C. Lee (HPCA, 2013)

DeSC: decoupled supply-compute communication management for heterogeneous architectures. - Tae Jun Ham; Juan L. Aragón; Margaret Martonosi (MICRO, 2015)

Graphicionado: A high-performance and energy-efficient accelerator for graph analytics. - Tae Jun Ham; Lisa Wu 001; Narayanan Sundaram; Nadathur Satish; Margaret Martonosi (MICRO, 2016)

Decoupling Data Supply from Computation for Latency-Tolerant Communication in Heterogeneous Architectures. - Tae Jun Ham; Juan L. Aragón; Margaret Martonosi (ACM Trans. Archit. Code Optim., 2017)

Data Access Optimization in Accelerator-Oriented Heterogeneous Architecture through Decoupling and Memory Hierarchy Specialization - Tae Jun Ham (2018)

Charon: Specialized Near-Memory Processing Architecture for Clearing Dead Objects in Memory. - Jaeyoung Jang; Jun Heo 001; Yejin Lee 001; Jaeyeon Won; Seonghak Kim; Sungjun Jung; Hakbeom Jang; Tae Jun Ham; Jae W. Lee (MICRO, 2019)

Practical Erase Suspension for Modern Low-latency SSDs. - Shine Kim; Jonghyun Bae; Hakbeom Jang; Wenjing Jin 001; Jeonghun Gong; SeungYeon Lee; Tae Jun Ham; Jae W. Lee (USENIX ATC, 2019)

Asynchronous I/O Stack: A Low-latency Kernel I/O Stack for Ultra-Low Latency SSDs. - Gyusun Lee; Seokha Shin; Wonsuk Song; Tae Jun Ham; Jae W. Lee; Jinkyu Jeong (USENIX ATC, 2019)

Eager Memory Management for In-Memory Data Analytics. - Hakbeom Jang; Jonghyun Bae; Tae Jun Ham; Jae W. Lee (IEICE Trans. Inf. Syst., 2019)

SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning. - Jonghyun Bae; Hakbeom Jang; Jeonghun Gong; Wenjing Jin 001; Shine Kim; Jaeyoung Jang; Tae Jun Ham; Jinkyu Jeong; Jae W. Lee (IEEE Micro, 2019)

Efficient Data Supply for Parallel Heterogeneous Architectures. - Tae Jun Ham; Juan L. Aragón; Margaret Martonosi (ACM Trans. Archit. Code Optim., 2019)

IIU: Specialized Architecture for Inverted Index Search. - Jun Heo 001; Jaeyeon Won; Yejin Lee 001; Shivam Bharuka; Jaeyoung Jang; Tae Jun Ham; Jae W. Lee (ASPLOS, 2020)

A3: Accelerating Attention Mechanisms in Neural Networks with Approximation. - Tae Jun Ham; Sungjun Jung; Seonghak Kim; Young H. Oh; Yeonhong Park; Yoonho Song; Jung-Hun Park; Sanghee Lee 002; Kyoung Park; Jae W. Lee; Deog-Kyoon Jeong (HPCA, 2020)

Unlocking Wordline-level Parallelism for Fast Inference on RRAM-based DNN Accelerator. - Yeonhong Park; Seung Yul Lee; Hoon Shin; Jun Heo 001; Tae Jun Ham; Jae W. Lee (ICCAD, 2020)

Genesis: A Hardware Acceleration Framework for Genomic Data Analysis. - Tae Jun Ham; David Bruns-Smith; Brendan Sweeney; Yejin Lee 001; Seong Hoon Seo; U. Gyeong Song; Young H. Oh; Krste Asanovic; Jae W. Lee; Lisa Wu Wills (ISCA, 2020)

A Specialized Architecture for Object Serialization with Applications to Big Data Analytics. - Jaeyoung Jang; Sungjun Jung; Sunmin Jeong; Jun Heo 001; Hoon Shin; Tae Jun Ham; Jae W. Lee (ISCA, 2020)

A Case for Hardware-Based Demand Paging. - Gyusun Lee; Wenjing Jin 001; Wonsuk Song; Jeonghun Gong; Jonghyun Bae; Tae Jun Ham; Jae W. Lee; Jinkyu Jeong (ISCA, 2020)

MosaicSim: A Lightweight, Modular Simulator for Heterogeneous Systems. - Opeoluwa Matthews; Aninda Manocha; Davide Giri; Marcelo Orenes-Vera; Esin Tureci; Tyler Sorensen 001; Tae Jun Ham; Juan L. Aragón; Luca P. Carloni; Margaret Martonosi (ISPASS, 2020)

Graphene: Strong yet Lightweight Row Hammer Protection. - Yeonhong Park; Woosuk Kwon; Eojin Lee; Tae Jun Ham; Jung Ho Ahn; Jae W. Lee (MICRO, 2020)

The MosaicSim Simulator (Full Technical Report). - Opeoluwa Matthews; Aninda Manocha; Davide Giri; Marcelo Orenes-Vera; Esin Tureci; Tyler Sorensen 001; Tae Jun Ham; Juan L. Aragón; Luca P. Carloni; Margaret Martonosi (CoRR, 2020)

MERCI: efficient embedding reduction on commodity hardware via sub-query memoization. - Yejin Lee 001; Seong Hoon Seo; Hyunji Choi; Hyoung Uk Sul; Soosung Kim 001; Jae W. Lee; Tae Jun Ham (ASPLOS, 2021)

FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks. - Jonghyun Bae; Jongsung Lee 001; Yunho Jin; Sam Son; Shine Kim; Hakbeom Jang; Tae Jun Ham; Jae W. Lee (FAST, 2021)

Behemoth: A Flash-centric Training Accelerator for Extreme-scale DNNs. - Shine Kim; Yunho Jin; Gina Sohn; Jonghyun Bae; Tae Jun Ham; Jae W. Lee (FAST, 2021)

Layerweaver: Maximizing Resource Utilization of Neural Processing Units via Layer-Wise Scheduling. - Young H. Oh; Seonghak Kim; Yunho Jin; Sam Son; Jonghyun Bae; Jongsung Lee 001; Yeonhong Park; Dong Uk Kim; Tae Jun Ham; Jae W. Lee (HPCA, 2021)

BOSS: Bandwidth-Optimized Search Accelerator for Storage-Class Memory. - Jun Heo 001; Seung Yul Lee; Sunhong Min; Yeonhong Park; Sungjun Jung; Tae Jun Ham; Jae W. Lee (ISCA, 2021)

ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks. - Tae Jun Ham; Yejin Lee 001; Seong Hoon Seo; Soosung Kim 001; Hyunji Choi; Sung Jun Jung; Jae W. Lee (ISCA, 2021)

MaPHeA: a lightweight memory hierarchy-aware profile-guided heap allocation framework. - Deok-Jae Oh; Yaebin Moon; Eojin Lee; Tae Jun Ham; Yongjun Park 001; Jae W. Lee; Jung Ho Ahn (LCTES, 2021)

ASAP: Fast Mobile Application Switch via Adaptive Prepaging. - Sam Son; Seung Yul Lee; Yunho Jin; Jonghyun Bae; Jinkyu Jeong; Tae Jun Ham; Jae W. Lee; Hongil Yoon (USENIX ATC, 2021)

Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework. - Tae Jun Ham; Yejin Lee 001; Seong Hoon Seo; U. Gyeong Song; Jae W. Lee; David Bruns-Smith; Brendan Sweeney; Krste Asanovic; Young H. Oh; Lisa Wu Wills (IEEE Micro, 2021)

L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training. - Jonghyun Bae; Woohyeon Baek; Tae Jun Ham; Jae W. Lee (ECCV (11), 2022)

Mithril: Cooperative Row Hammer Protection on Commodity DRAM Leveraging Managed Refresh. - Michael Jaemin Kim; Jaehyun Park 006; Yeonhong Park; Wanju Doh; Namhoon Kim; Tae Jun Ham; Jae W. Lee; Jung Ho Ahn (HPCA, 2022)

ANNA: Specialized Architecture for Approximate Nearest Neighbor Search. - Yejin Lee 001; Hyunji Choi; Sunhong Min; Hyunseung Lee 001; Sangwon Beak; Dawoon Jeong; Jae W. Lee; Tae Jun Ham (HPCA, 2022)

ULPPACK: Fast Sub-8-bit Matrix Multiply on Commodity SIMD Hardware. - Jaeyeon Won; Jeyeon Si; Sam Son; Tae Jun Ham; Jae W. Lee (MLSys, 2022)

Layerweaver+: A QoS-Aware Layer-Wise DNN Scheduler for Multi-Tenant Neural Processing Units. - Young H. Oh; Yunho Jin; Tae Jun Ham; Jae W. Lee (IEICE Trans. Inf. Syst., 2022)

Architecting a Flash-Based Storage System for Low-Cost Inference of Extreme-Scale DNNs. - Yunho Jin; Shine Kim; Tae Jun Ham; Jae W. Lee (IEEE Trans. Computers, 2022)

MaPHeA: A Framework for Lightweight Memory Hierarchy-aware Profile-guided Heap Allocation. - Deok-Jae Oh; Yaebin Moon; Do Kyu Ham; Tae Jun Ham; Yongjun Park 001; Jae W. Lee; Jung Ho Ahn; Eojin Lee (ACM Trans. Embed. Comput. Syst., 2023)

An LSM Tree Augmented with B+ Tree on Nonvolatile Memory. - Donguk Kim; Jongsung Lee 001; Keun Soo Lim; Jun Heo 001; Tae Jun Ham; Jae W. Lee (ACM Trans. Storage, 2024)

SkipLSM: Fast Retrieval of Hot Key-Value Pairs on LSM Tree. - Jongsung Lee 001; Sam Son; Jonghyun Bae; Yunho Jin; Tae Jun Ham; Jae W. Lee (SAC, 2025)