Master of Application Informatics
2021 - 2024
University of Göttingen, Germany
Master Thesis:
Improving the portability and interoperability of deep learning workloads using ONNX. Developed a supervised NLP classification model with the attention mechanism to automate the AI tasks in the GWDG ticket system. With a well-trained model, we cyclically update the model by retraining and inference with multiple programming languages on different devices. A cross-programming languages and devices framework has been established for federated learning and on-device learning with ONNX.
Research Intern
2023.10 - 2024.05
- Implemented a ResNet series deep learning framework using Golang with GPU utilization, optimizing the environment to eliminate dependency issues for execution within GWDG's cluster. Explored performance comparisons between this implementation and Python, as well as distributed learning implementations for this approach.
- Benchmark tests of IO500, HPL, HPCG, Stream and MiniBude for OpenMP, Julia, CUDA and OpenCL implementation
- High-Performance Computing practice for linux operations, cluster management and parallel computation by using MPI and CUDA. I built a distributed learning system from scratch by using Golang and MPI.