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Tae Jun Ham
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- affiliation: Seoul National University, Korea
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2020 – today
- 2024
- [j9]Donguk Kim
, Jongsung Lee
An LSM Tree Augmented with B+ Tree on Nonvolatile Memory. ACM Trans. Storage 20(1): 4:1-4:24 (2024) - 2023
- [j8]Deok-Jae Oh, Yaebin Moon, Do Kyu Ham, Tae Jun Ham, Yongjun Park, Jae W. Lee, Jung Ho Ahn, Eojin Lee:
MaPHeA: A Framework for Lightweight Memory Hierarchy-aware Profile-guided Heap Allocation. ACM Trans. Embed. Comput. Syst. 22(1): 2:1-2:28 (2023) - 2022
- [j7]Young H. Oh, Yunho Jin, Tae Jun Ham, Jae W. Lee:
Layerweaver+: A QoS-Aware Layer-Wise DNN Scheduler for Multi-Tenant Neural Processing Units. IEICE Trans. Inf. Syst. 105-D(2): 427-431 (2022) - [j6]Yunho Jin
Architecting a Flash-Based Storage System for Low-Cost Inference of Extreme-Scale DNNs. IEEE Trans. Computers 71(12): 3153-3164 (2022) - [c26]Jonghyun Bae, Woohyeon Baek
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training. ECCV (11) 2022: 171-188 - [c25]Yejin Lee, Hyunji Choi, Sunhong Min, Hyunseung Lee
ANNA: Specialized Architecture for Approximate Nearest Neighbor Search. HPCA 2022: 169-183 - [c24]Michael Jaemin Kim, Jaehyun Park
Mithril: Cooperative Row Hammer Protection on Commodity DRAM Leveraging Managed Refresh. HPCA 2022: 1156-1169 - [c23]Jaeyeon Won, Jeyeon Si, Sam Son, Tae Jun Ham, Jae W. Lee:
ULPPACK: Fast Sub-8-bit Matrix Multiply on Commodity SIMD Hardware. MLSys 2022 - [i4]Jonghyun Bae, Woohyeon Baek, Tae Jun Ham, Jae W. Lee:
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training. CoRR abs/2208.08711 (2022) - 2021
- [j5]Tae Jun Ham
Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework. IEEE Micro 41(3): 42-49 (2021) - [c22]Yejin Lee
MERCI: efficient embedding reduction on commodity hardware via sub-query memoization. ASPLOS 2021: 302-313 - [c21]Shine Kim, Yunho Jin, Gina Sohn, Jonghyun Bae, Tae Jun Ham, Jae W. Lee:
Behemoth: A Flash-centric Training Accelerator for Extreme-scale DNNs. FAST 2021: 371-385 - [c20]Jonghyun Bae, Jongsung Lee, Yunho Jin, Sam Son, Shine Kim, Hakbeom Jang, Tae Jun Ham, Jae W. Lee:
FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks. FAST 2021: 387-401 - [c19]Young H. Oh, Seonghak Kim, Yunho Jin, Sam Son, Jonghyun Bae, Jongsung Lee
Layerweaver: Maximizing Resource Utilization of Neural Processing Units via Layer-Wise Scheduling. HPCA 2021: 584-597 - [c18]Jun Heo, Seung Yul Lee, Sunhong Min, Yeonhong Park, Sungjun Jung, Tae Jun Ham, Jae W. Lee:
BOSS: Bandwidth-Optimized Search Accelerator for Storage-Class Memory. ISCA 2021: 279-291 - [c17]Tae Jun Ham, Yejin Lee, Seong Hoon Seo
ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks. ISCA 2021: 692-705 - [c16]Deok-Jae Oh
MaPHeA: a lightweight memory hierarchy-aware profile-guided heap allocation framework. LCTES 2021: 24-36 - [c15]Sam Son, Seung Yul Lee, Yunho Jin, Jonghyun Bae, Jinkyu Jeong, Tae Jun Ham, Jae W. Lee, Hongil Yoon:
ASAP: Fast Mobile Application Switch via Adaptive Prepaging. USENIX ATC 2021: 365-380 - [i3]Michael Jaemin Kim, Jaehyun Park, Yeonhong Park, Wanju Doh, Namhoon Kim, Tae Jun Ham, Jae W. Lee, Jung Ho Ahn:
Mithril: Cooperative Row Hammer Protection on Commodity DRAM Leveraging Managed Refresh. CoRR abs/2108.06703 (2021) - 2020
- [c14]Jun Heo, Jaeyeon Won, Yejin Lee, Shivam Bharuka, Jaeyoung Jang, Tae Jun Ham, Jae W. Lee:
IIU: Specialized Architecture for Inverted Index Search. ASPLOS 2020: 1233-1245 - [c13]Tae Jun Ham, Sungjun Jung, Seonghak Kim, Young H. Oh, Yeonhong Park, Yoonho Song
A3: Accelerating Attention Mechanisms in Neural Networks with Approximation. HPCA 2020: 328-341 - [c12]Yeonhong Park, Seung Yul Lee, Hoon Shin, Jun Heo, Tae Jun Ham, Jae W. Lee:
Unlocking Wordline-level Parallelism for Fast Inference on RRAM-based DNN Accelerator. ICCAD 2020: 103:1-103:9 - [c11]Tae Jun Ham, David Bruns-Smith, Brendan Sweeney, Yejin Lee, Seong Hoon Seo
Genesis: A Hardware Acceleration Framework for Genomic Data Analysis. ISCA 2020: 254-267 - [c10]Jaeyoung Jang, Sungjun Jung, Sunmin Jeong, Jun Heo, Hoon Shin, Tae Jun Ham, Jae W. Lee:
A Specialized Architecture for Object Serialization with Applications to Big Data Analytics. ISCA 2020: 322-334 - [c9]Gyusun Lee, Wenjing Jin, Wonsuk Song, Jeonghun Gong, Jonghyun Bae, Tae Jun Ham, Jae W. Lee, Jinkyu Jeong
A Case for Hardware-Based Demand Paging. ISCA 2020: 1103-1116 - [c8]Opeoluwa Matthews, Aninda Manocha, Davide Giri, Marcelo Orenes-Vera, Esin Tureci, Tyler Sorensen
MosaicSim: A Lightweight, Modular Simulator for Heterogeneous Systems. ISPASS 2020: 136-148 - [c7]Yeonhong Park, Woosuk Kwon, Eojin Lee, Tae Jun Ham, Jung Ho Ahn
Graphene: Strong yet Lightweight Row Hammer Protection. MICRO 2020: 1-13 - [i2]Tae Jun Ham, Sungjun Jung, Seonghak Kim, Young H. Oh, Yeonhong Park, Yoonho Song, Jung-Hun Park, Sanghee Lee, Kyoung Park, Jae W. Lee, Deog-Kyoon Jeong:
A3: Accelerating Attention Mechanisms in Neural Networks with Approximation. CoRR abs/2002.10941 (2020) - [i1]Opeoluwa Matthews, Aninda Manocha, Davide Giri, Marcelo Orenes-Vera, Esin Tureci, Tyler Sorensen, Tae Jun Ham, Juan L. Aragón, Luca P. Carloni, Margaret Martonosi:
The MosaicSim Simulator (Full Technical Report). CoRR abs/2004.07415 (2020)
2010 – 2019
- 2019
- [j4]Hakbeom Jang, Jonghyun Bae, Tae Jun Ham, Jae W. Lee:
Eager Memory Management for In-Memory Data Analytics. IEICE Trans. Inf. Syst. 102-D(3): 632-636 (2019) - [j3]Jonghyun Bae, Hakbeom Jang, Jeonghun Gong, Wenjing Jin, Shine Kim, Jaeyoung Jang, Tae Jun Ham, Jinkyu Jeong
SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning. IEEE Micro 39(5): 73-81 (2019) - [j2]Tae Jun Ham
Efficient Data Supply for Parallel Heterogeneous Architectures. ACM Trans. Archit. Code Optim. 16(2): 9:1-9:23 (2019) - [c6]Jaeyoung Jang, Jun Heo, Yejin Lee, Jaeyeon Won, Seonghak Kim, Sungjun Jung, Hakbeom Jang, Tae Jun Ham, Jae W. Lee:
Charon: Specialized Near-Memory Processing Architecture for Clearing Dead Objects in Memory. MICRO 2019: 726-739 - [c5]Gyusun Lee, Seokha Shin, Wonsuk Song, Tae Jun Ham, Jae W. Lee, Jinkyu Jeong:
Asynchronous I/O Stack: A Low-latency Kernel I/O Stack for Ultra-Low Latency SSDs. USENIX ATC 2019: 603-616 - [c4]Shine Kim, Jonghyun Bae, Hakbeom Jang, Wenjing Jin, Jeonghun Gong, SeungYeon Lee, Tae Jun Ham, Jae W. Lee:
Practical Erase Suspension for Modern Low-latency SSDs. USENIX ATC 2019: 813-820 - 2018
- [b1]Tae Jun Ham:
Data Access Optimization in Accelerator-Oriented Heterogeneous Architecture through Decoupling and Memory Hierarchy Specialization. Princeton University, USA, 2018 - 2017
- [j1]Tae Jun Ham
Decoupling Data Supply from Computation for Latency-Tolerant Communication in Heterogeneous Architectures. ACM Trans. Archit. Code Optim. 14(2): 16:1-16:27 (2017) - 2016
- [c3]Tae Jun Ham, Lisa Wu
Graphicionado: A high-performance and energy-efficient accelerator for graph analytics. MICRO 2016: 56:1-56:13 - 2015
- [c2]Tae Jun Ham, Juan L. Aragón
DeSC: decoupled supply-compute communication management for heterogeneous architectures. MICRO 2015: 191-203 - 2013
- [c1]Tae Jun Ham, Bharath K. Chelepalli, Neng Xue, Benjamin C. Lee:
Disintegrated control for energy-efficient and heterogeneous memory systems. HPCA 2013: 424-435
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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