Pei Mu
Student at The University of Edinburgh
City of Edinburgh, Scotland, United Kingdom
Summary
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Top SchoolPei Mu is a compiler engineer and MSc-by-Research student in compilers at the University of Edinburgh with nine years of experience building and researching compilers for AI hardware. They have four years of hands-on compiler engineering across Huawei, SenseTime and a Microsoft research internship, delivering code generation, IR design, passes and optimizations for architectures including Da‑Vinci, Ascend and Cambricon MLU. Notable contributions include a soft pipelining algorithm that yielded 1–2× performance gains, development of torch-mlir control-flow and extern_call features, and a BangC codegen pipeline for deep-inference chips. They also prototyped a polyhedral-model-based auto-scheduler and CUDA code-generation demo, reflecting a blend of production coding and academic research. Originally trained at Shandong University with a strong academic record, they now combine chip-aware compiler engineering with research-driven curiosity from Edinburgh.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE, 85.75(100), Bachelor of Engineering - BE, 85.75(100) at 山东大学MSc by Research, compilers, MSc by Research, compilers at 英国爱丁堡大学
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (97)
textbook10
ecosystem9
sql9
database9
database-management9
pytorch9
compiler8
music8
embedded-database8
faunadb8
duckdb8
postgresql8
music-composition8
machine-learning8
sensors8
Programming languages (8)
Github contributions (5)
PeiMu/easy_compiler
Jun 2021 - Jun 2022
Contributions:5 commits, 11 pushes, 1 branch in 1 year
PeiMu/torch-mlir
Nov 2021 - Apr 2023
The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.
Contributions:4 PRs, 49 pushes, 8 branches in 1 year 5 months
pytorchmlirdeep-learningtorchecosystem
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