Education
• Ph.D., Electrical and Computer Engineering
Georgia Tech, Atlanta, GA, USA
• B.S., Electrical and Electronic Engineering
Yonsei University, Seoul, South Korea
Work Experiences
• Associate Professor, School of Electrical and Electronic Engineering
Yonsei University, Seoul, South Korea
• Senior Engineer, Pre‑Silicon Quality & Design Reliability Team
Intel, Santa Clara, CA, USA
• Graduate Intern, Design for Power Team
Qualcomm, San Diego, CA, USA
• Graduate Co‑op, Power and Reliability‑Aware Microarchitecture Team
IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
• Graduate Co‑op, Research and Advanced Development Lab
AMD Research, Bellevue, WA, USA
• Graduate Intern, Computer Science Department
Sandia National Laboratories, Albuquerque, NM, USA
Research Interests
• Computer architecture and systems
• GPU microarchitecture
• Memory systems
• Neural network accelerators
• Power, thermal, and lifetime management
Awards
• Teaching Excellence Award
College of Engineering, Yonsei University (2024, 2022, 2020, 2018)
• Distinguished Faculty Award for Teaching Excellence
Yonsei University (2018)
• Best Student Paper Award
IEEE International Reliability Physics Symposium (2016)
• IBM/SRC Graduate Fellowship (2012‑2015)
Selected Publications
• T. Lim, H. Kim, J. Park, B. Kim, and W. Song, "RoTA: Rotational Torus Accelerator for Wear Leveling of Neural Processing Elements," Design, Automation and Test in Europe Conference (DATE), Mar. 2025
• Y. Kim and W. Song, "Genie Cache: Non‑blocking Miss Handling and Replacement in Page‑Table‑based DRAM Cache," IEEE/ACM International Symposium on Microarchitecture (MICRO), Nov. 2024, pp. 983-996
• H. Choi, C. Park, E. Kim, and W. Song, "Nona: Accurate Power Prediction Model Using Neural Networks," ACM/IEEE Design Automation Conference (DAC), no. 38, June 2024, pp. 1-6.
• C. Park, B. Kim, S. Ryu, and W. Song, "NeuroSpector: Systematic Optimization of Dataflow Scheduling in DNN Accelerators," IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 34, no. 8, Aug. 2023, pp. 2279-2294.
• H. Kim and W. Song, "LAS: Locality‑Aware Scheduling for GEMM‑Accelerated Convolutions in GPUs," IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 34, no. 5, May 2023, pp. 1479-1494.
• Y. Kim, H. Kim, and W. Song, "NOMAD: Enabling Non‑blocking OS‑Managed DRAM Cache via Tag‑Data Decoupling," IEEE International Symposium on High‑Performance Computer Architecture (HPCA), Feb. 2023, pp. 193-205.
• J. Lee, J. Lee, Y. Oh, W. Song, and W. Ro, "SnakeByte: A TLB Design with Adaptive and Recursive Page Merging in GPUs," IEEE International Symposium on High‑Performance Computer Architecture (HPCA), Feb. 2023, pp. 1195-1207.
• B. Kim, S. Lee, C. Park, H. Kim, and W. Song, "The Nebula Benchmark Suite: Implications of Lightweight Neural Networks," IEEE Transactions on Computers (TC), vol. 70, no. 11, Nov. 2021, pp. 1887‑1900.
• H. Kim, S. Ahn, B. Kim, Y. Oh, W. Ro, and W. Song, "Duplo: Lifting Redundant Memory Accesses of Deep Neural Networks for GPU Tensor Cores," IEEE/ACM International Symposium on Microarchitecture (MICRO), Oct. 2020, pp. 725‑737.
Selected Patents
• W. Song, B. Kim, C. Park, S. Koong, and T. Lim, "Deep Neural Network Accelerator for Optimized Data Processing and Control Method of the Deep Neural Network Accelerator," US12124879, Oct. 2024.
• W. Song, Y. Kim, and H. Kim, "DRAM Cache System and Operating Method of the Same," US18/627,459, Apr. 2024
• W. Song and H. Kim, "Neural Network Accelerator and Method of Controlling Same," US18/435,422, Feb. 2024.
• W. Song, C. Park, B. Kim, and S. Ryu, "Neural Network Computing Device and Control Method Thereof," US17/883,010, Aug. 2022.
• W. Song, W. Ro, H. Kim, S. Ahn, Y. Oh, and B. Kim, "Operation Device of Convolutional Neural Network, Operation Method of Convolutional Neural Network and Computer Program Stored in A Recording Medium to Execute the Method Thereof," US17/752,235, May 2022.
• S. O, W. Ro, W. Song, and J. Lee, "Controller, Computing System including the Same, and Method of Creating and Searching Page Table Entry for the Same," US11860793, Nov. 2021.
• R. Monfort, P. Bose, A. Buyuktosunoglu, C. Y. Cher, H. Jacobson, W. Song, K. Swaminathan, A. Vega, and L. Wang, "Optimization of Application Workflow in Mobile Embedded Devices," US10635490, Apr. 2020.
Software Frameworks
• C. Park, B. Kim, S. Ryu, and W. Song, "NeuroSpector: Dataflow and Mapping Optimization of Deep Neural Network Accelerators" (2023)
https://github.com/yonsei-icsl/NeuroSpector
• B. Kim, S. Lee, C. Park, H. Kim, and W. Song, "Nebula: Lightweight Neural Network Benchmarks" (2020)
https://github.com/yonsei-icsl/Nebula
• W. Song, "Kite: Architecture Simulator for RISC‑V Instruction Set" (2019)
https://github.com/yonsei-icsl/Kite