Yiyu Zhu is a Senior Software Engineer with 12 years of experience building high-performance systems at the intersection of software and hardware. Currently at NVIDIA, he focuses on CUDA acceleration for PyTorch training pipelines and has a track record designing bit-true hardware models and high-performance on-chip communication protocols. Proficient in C/C++, Python, Embedded Linux/RTOS, and Verilog, he brings deep expertise in optimization across software, firmware, and silicon verification. His background includes system engineering at Kneron and hands-on FPGA/Yocto board bring-up, reflecting a practical ability to move features from specification to silicon. Based in California with an M.Eng. in Communication Systems from UCSD, he’s also personally interested in distributed systems and control theory, often applying control-theoretic thinking to performance and resource optimization.
12 years of coding experience
3 years of employment as a software developer
Master of Engineering - MEng, Communication System, Master of Engineering - MEng, Communication System at University of California San Diego
Bachelor of Science (B.S.), Electrical and Electronics Engineering, Bachelor of Science (B.S.), Electrical and Electronics Engineering at University of California, San Diego
The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate
Contributions:46 pushes, 5 branches in 20 days
pytorchpythonboilerplatedata-sciencedeep-learning
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