Shiqing Fan
Senior Performance Architect at NVIDIA
Pudong, Shanghai, China
Summary
👤
Senior🎓
Top SchoolShiqing Fan is a Senior Performance Architect at NVIDIA with 11 years of experience optimizing end-to-end LLM training stacks and large-scale distributed ML workloads. He combines deep systems and parallel-algorithms expertise from his masters work with hands-on platform engineering at Alibaba—where he led and open-sourced DAPPLE and contributed to automatic parallelization, DistributionStrategy and model-parallel solutions for industry-scale training. At NVIDIA he focuses on full-stack training optimizations for Megatron-LM-class systems, bringing hardware-aware compute architecture insights to software pipelines. His open-source contributions span both compute-heavy projects and infrastructure quality improvements, including code-cleanup and metadata optimizations in Alluxio. Based in Pudong, Shanghai, he is notable for blending rigorous academic foundations (top of class at Nanjing University) with pragmatic production engineering across cloud, interconnect-aware GPU clusters and compiler-driven parallelization.
11 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science and Technology, 4.51/5，6/179, Bachelor's degree, Computer Science and Technology, 4.51/5，6/179 at Nanjing UniversityJiangSu XinHai Senior High School
English, Chinese
Stackoverflow
688reputation
482kreached
4answers
2questions
Github Skills (15)
javas10
code-optimization10
back-end-development10
java10
data-structures8
data-structure8
alluxio8
orchestrate7
orchestration7
vector6
generics6
linux6
hadoop6
ssh6
r6
Programming languages (8)
Github contributions (5)
Alluxio/alluxio
Jul 2015 - Apr 2017
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
Back-end Developer
Back-end DeveloperContributions:74 commits, 54 PRs, 78 comments in 1 year 10 months
Contributions summary:Shiqing primarily focused on code cleanup and optimization tasks within the Tachyon project. Their contributions involved removing unused variables and imports, as well as refactoring and improving the efficiency of existing code, specifically within the block metadata management components. They also made several small fixes and improvements to comments and documentation. These changes suggest a focus on code quality and maintainability.
data-analysisvirtual-distributed-filesystemanalyticsorchestrationdata-science
fanshiqing/fanshiqing.github.io
Jun 2017 - Jun 2018
Contributions:48 pushes, 1 branch in 1 year
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