Research Interest

Computer systems and architecture, heterogeneous computing, mobile computing, neural network accelerators, performance characterization, power and energy efficiency

Education

Ph.D. in Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea (Feb. 2025 (anticipated))

B.S. in Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea (Aug. 2018)

Publications

B. Kim, C. Park, H. Kim, K. Rao, and W. J. Song, "NPUsim: Full-System, Cycle-Accurate, Value-Aware Functional Simulations of DNN Accelerators", Under revision.

T.Lim, H. Kim, J. Park, B. Kim, and W. Song, "RoTA: Rotational Torus Accelerator for Wear Leveling of Neural Processing Elements", Deisgn, Automation and Test in Europe Conference, Mar. 2025, To appear

C. Park*, B. Kim*, S. Ryu, and W. J. Song, (*equal contribution)"NeuroSpector: Systematic Optimization of Dataflow Scheduling in Deep Neural Network Accelerators", IEEE Transactions on Parallel and Distributed Computing, vol.34, no.8, Aug. 2023, pp.2279-2294

B. Kim, S. Lee, A. Trivedi, and W. J. Song, "Energy-Efficient Acceleration of Neural Network Applications on Edge Devices", IEEE Access, vol. 8, Nov. 2020, pp.216259-216270.

B. Kim, S. Lee, C. Park, H. Kim, and W. J. Song, "The Nebula Benchmark Suite: Implications of Lightweight Neural Networks", IEEE Transactions on Computers, vol. 70, Oct. 2020, pp.1887-1900.

H. Kim, S. Ahn, Y. Oh, B. Kim, W. Ro, and W. J. Song, "Duplo: Lifting Redundant Memory Accesses of Deep Neural Networks for GPU Tensor Cores", The 53rd IEEE/ACM International Symposium on Microarchitecture, Oct. 2020, pp.364-379.

Workshops

B. Kim, C. Park, T. Lim, and W. J. Song, "NPUsim: Full-System, Cycle-Accurate, Functional Simulations of Deep Neural Network Accelerators", Workshop on Modeling and Simulation of Systems and Applications, Oct. 2021.

B. Kim, S. Lee, and W. J. Song, "Nebula: Lightweight Neural Network Benchmarks", Workshop on Modeling and Simulation of Systems and Applications, Aug. 2020.

Poster

C. Park, S. Koong, B. Kim, T. Lim, and W. J. Song, "Fornax: Lightweight Energy-Efficient DNN Accelerator Architecture for Edge Devices", IEEE/ACM Design Automation Conference, Work-in-Progress (WIP), July, 2023.

T. Lim, H. Kim, J. Park, B. Kim, and W. J. Song "Wear Leveling of Processing Element Arrays in Deep Neural Network Accelerators", IEEE/ACM Design Automation Conference, Work-in-Progress (WIP), July, 2023.

Software

NPUsim: A Full-System NPU Microarchitecture Simulation Framework

NeuroSpector: Dataflow and Mapping Optimization of Deep Neural Network Accelerators.

Nebula: Lightweight Neural Network Benchmarks.

Patents

W. J. 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,” US18/127,875, Mar., 2023.

W. J. Song, C. Park, B. Kim, and S. Ryu, "Neural Network Computing Device and Control Method,” US17/883,010, Aug., 2022.

W. J. Song, B. Kim, and S. Lee, "Operation Device of Artificial Neural Network, Operation Method of Artificial Neural Network and Computer Program Stored in A Recording Medium to Execute The Method," 10-2021-0071874, June 2021.

W. J. 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 Recording Medium to Execute The Method," 10-2021-0066176, May 2021.

Scholarship

Ph.D. Fellowship
National Research Foundation of Korea (June 2021 - May 2023)