[IEEE Journal of Solid-State Circuits (JSSC), 2024] Junsoo Kim’s paper on EPU: An Energy-Efficient Explainable AI Accelerator with Sparsity-free Computation and Heat Map Compression/Pruning is accepted

Congratulations! We have a paper accepted to Journal of Solid-State Circuits (JSSC), 2024 “EPU: An Energy-Efficient Explainable AI Accelerator with Sparsity-free Computation and Heat Map Compression/Pruning” Junsoo Kim, Seunghee Han, Geonwoo Ko, Ji-Hoon Kim, Changha Lee, Taewoo Kim, Chan-Hyun Youn, and Joo-Young Kim

[IEEE Access 2024] Ji-Hoon Kim’s paper on Trinity: In-Database Near-data Machine Learning Acceleration Platform for Advanced Data Analytics is accepted

Congratulations! We have a paper accepted to IEEE Access, 2024. “Trinity: In-Database Near-data Machine Learning Acceleration Platform for Advanced Data Analytics is accepted” Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji, Joo-Young Kim

[IEEE International Symposium on High-Performance Computer Architecture 2024] Prasetiyo’s paper on Throughput-Maximized TFHE-based Accelerator is accepted

Congratulations! We have a paper accepted to IEEE International Symposium on High-Performance Computer Architecture, 2024 “Morphling: A Throughput-Maximized TFHE-based Accelerator using Transform-domain Reuse ” Prasetiyo, Adiwena Putra, and Joo-young Kim

[Asia and South Pacific Design Automation Conference 2024] Jinho Yang’s paper on FPGA-based Embedded Vision Platform is accepted

Congratulations! We have a paper accepted to Asia and South Pacific Design Automation Conference , 2024 “ACane: An Efficient FPGA-based Embedded Vision Platform with Accumulation-as-Convolution Packing for Autonomous Mobile Robots ” Jinho Yang, Sungwoong Yune, Sukbin Lim, Donghyuk Kim, and Joo-Young Kim

[IEEE/ACM International Symposium on Microarchitecture 2023] Adiwena Putra’s paper on Homomorphic Encryption is accepted

Congratulations! We have a paper accepted to IEEE/ACM International Symposium on Microarchitecture, 2023 “Strix: An End-to-End Streaming Architecture with Two-Level Ciphertext Batching for Fully Homomorphic Encryption with Programmable Bootstrapping” Adiwena Putra, Prasetiyo, Yi Chen, John Kim, and Joo-Young Kim

[IEEE/ACM International Conference on Computer-Aided Design 2023] Jaehoon Heo’s paper on Processing-in-DRAM Emulation Framework is accepted

Congratulations! We have a paper accepted to IEEE/ACM International Conference on Computer-Aided Design, 2023 “PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads” Jaehoon Heo, Yongwon Shin, Sangjin Choi, Sungwoong Yune, Jung-Hoon Kim, Hyojin Sung, Youngjin Kwon, and Joo-Young Kim

[Communications of the ACM 2023] Ji-Hoon Kim’s paper on AI Semiconductor Inductry is accepted

Congratulations! We have a paper accepted to Communications of the ACM, 2023 ” South Korea’s Nationwide Effort for AI Semiconductor Industry ” Ji-Hoon Kim, Sungyeob Yoo, and Joo-Young Kim

[ESSCIRC 2023] Je Yang’s paper on Joint-DNN Training Processor is accepted

Congratulations! We have a paper accepted to IEEE European Solid-State Circuits Conference (ESSCIRC), 2023 ” JNPU: A 1.04TFLOPS Joint-DNN Training Processor with Speculative Cyclic Quantization and Triple Heterogeneity on Microarchitecture / Precision / Dataflow ” Je Yang, Sukbin Lim, Sukjin Lee, Jae-Young Kim and Joo-Young Kim

[Hotchips 2023] Seungjae Moon’s paper on Accelerating Hyperscale Models for Generative AI is accepted

Congratulations! We have a paper accepted to Symposium on High Performance Chips (HotChips), 2023. ” HyperAccel LPU: Accelerating Hyperscale Models for Generative AI ” Seungjae Moon, Junsoo Kim, Jung-Hoon Kim, Junseo Cha, Gyubin Choi, Seongmin Hong and Joo-Young Kim

[VLSI 2023] Junghoon Kim and Jaehoon Heo’s paper on Super-Pipelined Processing-In-Memory Accelerator is accepted

Congratulations! We have a paper accepted to the International Conference on Symposium on VLSI Technology and Circuits (VLSI), 2023. “SP-PIM: A 22.41TFLOPS/W, 8.81Epochs/Sec Super-Pipelined Processing-In-Memory Accelerator with Local Error Prediction for On-Device Learning” *Jung-Hoon Kim, *Jaehoon Heo, Wontak Han, Jaeuk Kim and Joo-Young Kim (*equal contribution)