4 citations · 4 across the 5 of their papers we have counts for
5 papers
AI-PROPELLER: Warehouse-Scale Interprocedural Code Layout Optimization with AlphaEvolve
Chaitanya Mamatha Ananda, Rajiv Gupta, Mircea Trofin +4
Post-link optimizers (PLOs) such as Propeller and BOLT have demonstrated that precise, profile-guided code layout can extract significant performance gains from heavily optimized b…
Magellan: Autonomous Discovery of Novel Compiler Optimization Heuristics with AlphaEvolve
Hongzheng Chen, Alexander Novikov, Ngân Vũ +5
Modern compilers rely on hand-crafted heuristics to guide optimization passes. These human-designed rules often struggle to adapt to the complexity of modern software and hardware…
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization
Teodor V. Marinov, Alekh Agarwal, Mircea Trofin
This work studies a Reinforcement Learning (RL) problem in which we are given a set of trajectories collected with K baseline policies. Each of these policies can be quite suboptim…
The Next 700 ML-Enabled Compiler Optimizations
S. VenkataKeerthy, Siddharth Jain, Umesh Kalvakuntla +6
There is a growing interest in enhancing compiler optimizations with ML models, yet interactions between compilers and ML frameworks remain challenging. Some optimizations require…
ComPile: A Large IR Dataset from Production Sources
Aiden Grossman, Ludger Paehler, Konstantinos Parasyris +6
Code is increasingly becoming a core data modality of modern machine learning research impacting not only the way we write code with conversational agents like OpenAI's ChatGPT, Go…