Superoptimization

Abstract: We consider the problem of synthesizing loop-free programs that implement a desired functionality using components from a given library. Specifications of the desired functionality and the library components are provided as logical relations between their respective input and output variables. The library components can be used at most once, and hence the library is required to contain a reasonable overapproximation of the multiset of the components required.We solve the above component-based synthesis problem using a constraint-based approach that involves first generating a synthesis constraint, and then solving the constraint. The synthesis constraint is a first-order ∃∀ logic formula whose size is quadratic in the number of components. We present a novel algorithm for solving such constraints. Our algorithm is based on counterexample guided iterative synthesis paradigm and uses off-the-shelf SMT solvers.We present experimental results that show that our tool Brahma can efficiently synthesize highly nontrivial 10-20 line loop-free bitvector programs. These programs represent a state space of approximately 2010 programs, and are beyond the reach of the other tools based on sketching and superoptimization.

Abstract: The Java HotSpotTM Server Compiler achieves improved asymptotic performance through a combination of object-oriented and classical-compiler optimizations. Aggressive inlining using class-hierarchy analysis reduces function call overhead and provides opportunities for many compiler optimizations.

Abstract: Applying the right compiler optimizations to a particular program can have a significant impact on program performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using performance counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our performance counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.

Abstract: A "Just-In-Time" (JIT) Java compiler produces native code from Java byte code instructions during program execution. As such, compilation speed is more important in a Java JIT compiler than in a traditional compiler, requiring optimization algorithms to be lightweight and effective. We present the structure of a Java JIT compiler for the Intel Architecture, describe the lightweight implementation of JIT compiler optimizations (e.g., common subexpression elimination, register allocation, and elimination of array bounds checking), and evaluate the performance benefits and tradeoffs of the optimizations. This JIT compiler has been shipped with version 2.5 of Intel's VTune for Java product.