Xinliang David Li
David is a Principal Engineer at Google. He manages the Compiler Optimization Team and leads the effort to generate the fastest possible code for Google's data center softwares. His research interests include highly scalable cross module optimizations, scalable profile guided optimizations (instrumentation, PMU sample, trace-based), memory hierarchy optimizations (data and instructions), micro-architecture optimizations, post link optimizations, and ML based optimization frameworks.
Authored Publications
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Google
PreFix: Optimizing the Performance of Heap-Intensive Applications
Chaitanya Mamatha Ananda
Rajiv Gupta
Han Shen
CGO 2025: International Symposium on Code Generation and Optimization, Las Vegas, NV, USA (to appear)
Propeller: A Profile Guided, Relinking Optimizer for Warehouse-Scale Applications
Han Shen
Rahman Lavaee
ACM, pp. 617-631
automemcpy: A framework for automatic generation of fundamental memory operations
Sam Xi
Proceedings of the 2021 ACM SIGPLAN International Symposium on Memory Management (ISMM '21), June 22, 2021, Virtual, Canada (to appear)
AutoFDO: Automatic Feedback-Directed Optimization for Warehouse-Scale Applications
Dehao Chen
CGO 2016 Proceedings of the 2016 International Symposium on Code Generation and Optimization, ACM, New York, NY, USA, pp. 12-23
Automated locality optimization based on the reuse distance of string operations
Preview
Silvius Rus
Raksit Ashok
CGO '11 Proceedings of the 9th Annual IEEE/ACM International Symposium on Code Generation and Optimization, IEEE Computer Society, Washington, DC, USA (2011), pp. 181-190
Safe ICF: Pointer Safe and Unwinding Aware Identical Code Folding in Gold
Cary Coutant
Chris Demetriou
GCC Developers Summit (2010)
