Backwards Data-Flow Analysis using Prophecy Variables in the BuildIt System

TL;DR

This paper introduces prophecy variables in BuildIt, a system that enables future-aware program transformations and optimizations without traditional backwards analysis, reducing engineering effort and improving performance.

Contribution

It formalizes prophecy variables for forward execution-based analysis, integrating them into BuildIt to enhance program optimization capabilities.

Findings

Prophecy variables enable future-aware optimizations in BuildIt.

Repeated forward execution with prophecy variables improves performance.

The approach reduces engineering effort compared to traditional backwards analysis.

Abstract

Many program transformations and optimizations require information about the future behavior of the program. A standard way to obtain this information is to build an intermediate program representation, then use a backwards program analysis to propagate relevant information against the flow of control back to the transformation/optimization site. We instead propose to use prophecy variables, which predict information about the future execution of the program, to enable such transformations and optimizations. We implement prophecy variables in BuildIt, a lightweight domain specific language implementation system. BuildIt uses staged compilation to implement high performance domain specific languages embedded within a standard general purpose programming language (C++). The BuildIt first phase uses standard C++ program execution to generate optimized C, C++, and CUDA second phase code. This approach enables BuildIt to eliminate programming language implementation components such as parsers and intermediate representations, delivering a dramatic decrease in the engineering effort required to implement domain specific languages. The combination of prophecy variables and repeated forward program execution enables BuildIt to extend this approach to include transformations and optimizations that require information about the future execution of the program without backwards analyses and without the engineering overhead associated with implementing these analyses. We formalize the use of prophecy variables for this purpose, discuss the implementation of prophecy variables and repeated execution in BuildIt, and present experimental results for BuildIt computations that benefit from optimizations enabled by the information that prophecy variables provide.