Publications
Works done during my Ph.D.
Yi-Chien Lin, Ronald Pineda, and Fanny Nina Paravecino. “APEX: An Extensible and Dynamism-Aware Simulator for Automated Parallel Execution in LLM Serving,” Journal of Parallel and Distributed Computing (JPDC), 2026 [To Appear].
Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, and Viktor Prasanna. “ARGO+: Achieving Multi-Level Scalable GNN Training on Distributed Multi-Core Platform,” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2026.
Yi-Chien Lin, Haoyang Fan, Sameh Gobriel, Nilesh Jain, and Viktor K. Prasanna. “Accelerating GNN Inference via Automated Parallel Execution on Edge Heterogeneous Platforms,” International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2025.
Rakshith Jayanth, Yi-Chien Lin, Souvik Kundu, Deepak A. Mathaikutty, and Viktor Prasanna. “ACCLAIM: Accelerating Long Context LLM Inference on Heterogeneous Edge Platforms,” The Latin America High Performance Computing (CARLA), 2025.
Haoyang Fan, Yi-Chien Lin, Viktor Prasanna. “ELLIE: Energy-Efficient LLM Inference at the Edge Via Prefill-Decode Splitting,” International Conference on Application Specific Systems, Architectures and Processors (ASAP), 2025.
Sachini Wickramasinghe, Yi-Chien Lin, Cauligi Raghavendra, Viktor Prasanna. “SMART: High-Performance SAR ATR Through Model-Architecture Co-Design on FPGA,” IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM), 2025.
Yi-Chien Lin, Zhijie Xu, Viktor Prasanna, “xBS-GNN: Accelerating Billion-Scale GNN Training on FPGA,” Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W), 2024.
Yi-Chien Lin, Gangda Deng, Viktor Prasanna, “A Unified CPU-GPU Protocol for GNN Training,” 21st ACM International Conference on Computing Frontiers (CF), 2024
Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, Gopi Krishna Jha, Viktor Prasanna, “ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor,” IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2024 [Best Paper Nominee]
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna, “HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform,” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2024
Yi-Chien Lin, Viktor Prasanna, “HyScale-GNN: A Scalable Hybrid GNN Training System on Single-Node Heterogeneous Architecture,” IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2023
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna, “Accelerating GNN Training on CPU+Multi-FPGA Heterogeneous Platform,” The Latin America High Performance Computing (CARLA), 2022
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna, “HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous Platform,” International Symposium on Field-Programmable Gate Arrays (FPGA), 2022
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna, “GCN Inference Acceleration using High-Level Synthesis,” IEEE High Performance Extreme Computing Conference (HPEC), 2021
Works done during my undergrad
Yi-Chien Lin, Chih-Hung Lin, Ling-Yu Wu, Chih-Shiuan Lee, “Face Orientation-Based Cursor Positioning on Display Screens,” WIPO Patent No. WO/2021/145855, 2021
Jing-Ping Wu, Yi-Chien Lin, Ying-Wei Wu, Shih-Wei Hsieh, Ching-Hsuan Tai, and Yi-Chang Lu., “A Memory-Efficient Accelerator for DNA Sequence Alignment with Two-Piece Affine Gap Tracebacks,” IEEE International Symposium on Circuits and Systems (ISCAS), 2021