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Hou Yuteng侯宇腾

High-performance kernels on ARM SME/SVE, and AI systems that actually run. Graduated from Harbin Institute of Technology, Shenzhen, and KU Leuven (Cum Laude).

GEMM and attention on ARM SME/SVE, and HPC, AI agents, and model deployment brought together into systems that run.

  • 01 ARM / HPC

    UniGEMM, GEMM, and attention on SME/SVE

  • 02 AI agents

    Tool use, remote execution, and agent workflows

  • 03 Model deployment

    Local inference, ARM platforms, and performance checks

Education

  • 2019–2024Harbin Institute of Technology, Shenzhen · B.Eng. in Electronics and Information Engineering
  • 2021–2023KU Leuven · B.Sc. in Engineering Technology, joint program
  • 2023–2024KU Leuven · M.Sc. in Engineering Technology, Software Systems · Cum Laude

Experience

  • 2025–presentUniGEMM, GEMM, and attention on ARM SME/SVE: multi-precision assembly generation, core GEMM kernels above 95% of theoretical peak, and memory-access and compute optimizations across several attention variants.
  • Same periodMPI and UCX performance work in HPC settings, and maintenance of KBLAS and Eigen.
  • 2023–2024Stability after model deployment: monitoring input distributions and output anomalies to reduce concept drift.

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GitHub · @0tomhoyt