Machine Learning in Compiler Optimization By Namita Dave

Overview What are compiler optimizations? Challenges with optimizations Current Solutions Machine learning techniques Structure of Adaptive compilers

Introduction Optimization refers to process of modifying to achieve maximum efficiency in terms of storage, cost or time. Machine learning techniques can be effectively used for optimizing based on specifics of program and target platform

Challenges Inherently hard Problems Interactions between optimizations

Inherently hard problems Due to the interaction of compiler optimization with the hardware Example – Register allocation

Interaction between optimizations There can be positive or negative interactions It depends in the order in which optimizations are applied Positive Interaction Example GCSE and Loop unrolling Negative interaction example Instruction scheduling and Register allocation

Instruction Scheduling vs Register Allocation z = x[i] tmp = x[i+1+n] Pre pass Post Pass

Current Solutions Employ Heuristics To decide whether to apply an optimization or not Example – In lining decisions Phase ordering To decide the sequence of optimizations so as to minimize negative interactions

Typical Optimizing compiler

Problem? Compiler Heuristics and Phase ordering is manual and predetermined The solution needs to be dependent on specifics of program and the target platform

Solution Using machine learning techniques, a near optimal solution can be developed.

Heuristic selection Machine learning techniques like supervised classification, function approximation and function selection can be employed for heuristic selection Example Supervised classification can be used to predict best unroll loop factor Genetic programming can be used for learning priority functions

Automatic Phase Ordering Unsupervised learning techniques can automate phase ordering Based on the notion of similarity of programs Offline training data can be used to identify a set of best phase orderings for similar programs Based on feature vectors, similar programs can be found for a given new program

Structure of Adaptive compiler

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