Browsing by Titles

Showing results 1 to 16 of 16

  • 2024-11-19
  • Choi, Dong-Gu. (2024-11-19). A 65nm 687.5-TOPS/W Drive Strength-based SRAM Compute-In-Memory Macro with Adaptive Dynamic Range for Edge AI applications. IEEE Asian Solid-State Circuits Conference. doi: 10.1109/A-SSCC60305.2024.10848920
  • IEEE Solid-State Circuits Society
  • View : 266
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  • Jung, Sangwoo
  • Lee, Jaehyun
  • Park, Dahoon
  • Lee, Youngjoo
  • Yoon, Jong-Hyeok
  • Kung, Jaeha
  • 2024-12
  • Jung, Sangwoo. (2024-12). A Dual-Precision and Low-Power CNN Inference Engine Using a Heterogeneous Processing-in-Memory Architecture. IEEE Transactions on Circuits and Systems I: Regular Papers, 71(12), 5546–5559. doi: 10.1109/TCSI.2024.3395842
  • Institute of Electrical and Electronics Engineers
  • View : 191
  • Download : 0
  • Jeong, Seonghun
  • Lee, Jooyeon
  • Kung, Jaeha
  • 2024-01-29
  • Jeong, Seonghun. (2024-01-29). A Full SW-HW Demonstration of GEMM Accelerators with RISC-V Instruction Extensions. 23rd International Conference on Electronics, Information, and Communication, ICEIC 2024, 1–3. doi: 10.1109/ICEIC61013.2024.10457251
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 37
  • Download : 0
  • Lee, Jooyeon
  • Lee, Donghun
  • Kung, Jaeha
  • 2024-05-20
  • Lee, Jooyeon. (2024-05-20). A Ready-to-Use RTL Generator for Systolic Tensor Arrays and Analysis Using Open-Source EDA Tools. IEEE International Symposium on Circuits and Systems (ISCAS 2024), 1–5. doi: 10.1109/ISCAS58744.2024.10558043
  • IEEE Circuits and Systems Society
  • View : 82
  • Download : 0
  • Noh, Seock-Hwan
  • Lee, Seungpyo
  • Shin, Banseok
  • Park, Sehun
  • Jang, Yongjoo
  • Kung, Jaeha
  • 2025-05
  • Noh, Seock-Hwan. (2025-05). All-Rounder: A Flexible AI Accelerator With Diverse Data Format Support and Morphable Structure for Multi-DNN Processing. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 33(5), 1264–1277. doi: 10.1109/TVLSI.2025.3540346
  • Institute of Electrical and Electronics Engineers
  • View : 44
  • Download : 0
  • Lee, Seunghyun
  • Choi, Jeik
  • Noh, Seockhwan
  • Koo, Jahyun
  • Kung, Jaeha
  • 2023-07-11
  • Lee, Seunghyun. (2023-07-11). DBPS: Dynamic Block Size and Precision Scaling for Efficient DNN Training Supported by RISC-V ISA Extensions. Design Automation Conference, 23709289. doi: 10.1109/DAC56929.2023.10248013
  • ACM Special Interest Group on Design Automation (SIGDA), IEEE Council on Electronic Design Automation (CEDA)
  • View : 109
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  • Noh, Seockhwan
  • Koo, Jahyun
  • Lee, Seunghyun
  • Park, Jongse
  • Kung, Jaeha
  • 2023-09
  • Noh, Seockhwan. (2023-09). FlexBlock: A Flexible DNN Training Accelerator with Multi-Mode Block Floating Point Support. IEEE Transactions on Computers, 72(9), 2522–2535. doi: 10.1109/TC.2023.3253050
  • IEEE Computer Society
  • View : 87
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  • Noh, Seock-Hwan
  • Shin, Banseok
  • Choi, Jeik
  • Lee, Seungpyo
  • Kung, Jaeha
  • Kim, Yeseong
  • 2025-06-25
  • Noh, Seock-Hwan. (2025-06-25). FlexNeRFer: A Multi-Dataflow, Adaptive Sparsity-Aware Accelerator for On-Device NeRF Rendering. ACM/IEEE International Symposium on Computer Architecture, 1894–1909. doi: 10.1145/3695053.3731107
  • ACM, IEEE
  • View : 243
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  • Shin, Banseok
  • Park, Sehun
  • Kung, Jaeha
  • 2023-06-27
  • Shin, Banseok. (2023-06-27). Improving Hardware Efficiency of a Sparse Training Accelerator by Restructuring a Reduction Network. IEEE Interregional NEWCAS Conference, NEWCAS 2023, 191480. doi: 10.1109/NEWCAS57931.2023.10198090
  • IEEE CAS Society
  • View : 85
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NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage

  • 2024-05-01
  • Kim, Jungwoo. (2024-05-01). NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage. Architectural Support for Programming Languages and Operating Systems, 689–707. doi: 10.1145/3620666.3651345
  • Association for Computing Machinery
  • View : 298
  • Download : 44
  • Hwang, Sangwoo
  • Kung, Jaeha
  • 2025-01
  • Hwang, Sangwoo. (2025-01). One-Spike SNN: Single-Spike Phase Coding With Base Manipulation for ANN-to-SNN Conversion Loss Minimization. IEEE Transactions on Emerging Topics in Computing, 13(1), 162–172. doi: 10.1109/TETC.2024.3386893
  • IEEE Computer Society
  • View : 77
  • Download : 0
  • Koo, Jahyun
  • Park, Dahoon
  • Jung, Sangwoo
  • Kung, Jaeha
  • 2024-06-25
  • Koo, Jahyun. (2024-06-25). OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models. Design Automation Conference, 1–6. doi: 10.1145/3649329.3657323
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 63
  • Download : 0
  • 2023-08
  • Hwang, Sangwoo. (2023-08). ReplaceNet: real-time replacement of a biological neural circuit with a hardware-assisted spiking neural network. Frontiers in Neuroscience, 17. doi: 10.3389/fnins.2023.1161592
  • Frontiers
  • View : 238
  • Download : 27
  • Kang, Gunil
  • Park, Dahoon
  • Lee, Hojin
  • Jung, Sangwoo
  • Park, Jiyong
  • Min, Jung Gyu
  • Lee, Youngjoo
  • Kung, Jaeha
  • 2025-01-23
  • Kang, Gunil. (2025-01-23). RISC-V Driven Orchestration of Vector Processing Units and eFlash Compute-in-Memory Arrays for Fast and Accurate Keyword Spotting. 30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025, 1174–1180. doi: 10.1145/3658617.3697697
  • Association for Computing Machinery
  • View : 231
  • Download : 0

Skipformer: Evolving Beyond Blocks for Extensively Searching On-Device Language Models With Learnable Attention Window

  • Bodenham, Matthew
  • Kung, Jaeha
  • 2024-09
  • Bodenham, Matthew. (2024-09). Skipformer: Evolving Beyond Blocks for Extensively Searching On-Device Language Models With Learnable Attention Window. IEEE Access, 12, 124428–124439. doi: 10.1109/ACCESS.2024.3420232
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 89
  • Download : 25
  • Hwang, Sangwoo
  • Lee, Seunghyun
  • Park, Dahoon
  • Lee, Donghun
  • Kung, Jaeha
  • 2024-12-13
  • Hwang, Sangwoo. (2024-12-13). SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation. Conference on Neural Information Processing Systems (poster), 1–24.
  • Neural Information Processing Systems Foundation (NeurIPS Foundation)
  • View : 215
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