Hyungyo Kim
Orcid: 0000-0002-1157-0127
According to our database1,
Hyungyo Kim authored at least 14 papers
between 2021 and 2026.
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Bibliography
2026
Characterizing the Intrinsic Bank-Level Accuracy Versus Energy Trade-Off of SRAM-Based Analog In-Memory Computing Architectures in 28 nm CMOS.
IEEE Trans. Circuits Syst. I Regul. Pap., February, 2026
LiLo: Harnessing the on-Chip Accelerators in Intel CPUs for Compressed LLM Inference Acceleration.
Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2026
2025
The New LLM Bottleneck: A Systems Perspective on Latent Attention and Mixture-of-Experts.
CoRR, July, 2025
Stratum: System-Hardware Co-Design with Tiered Monolithic 3D-Stackable DRAM for Efficient MoE Serving.
Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025
NetZIP: Algorithm/Hardware Co-design of In-network Lossless Compression for Distributed Large Model Training.
Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025
LIA: A Single-GPU LLM Inference Acceleration with Cooperative AMX-Enabled CPU-GPU Computation and CXL Offloading.
Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025
2024
Enhancing the Accuracy of 6T SRAM-Based In-Memory Architecture via Maximum Likelihood Detection.
IEEE Trans. Signal Process., 2024
Exploiting Intel Advanced Matrix Extensions (AMX) for Large Language Model Inference.
IEEE Comput. Archit. Lett., 2024
An LPDDR-based CXL-PNM Platform for TCO-efficient Inference of Transformer-based Large Language Models.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024
2023
Boosting the Accuracy of SRAM-Based in-Memory Architectures Via Maximum Likelihood-Based Error Compensation Method.
Proceedings of the IEEE International Conference on Acoustics, 2023
2021
Direct Gradient Calculation: Simple and Variation-Tolerant On-Chip Training Method for Neural Networks.
Adv. Intell. Syst., 2021