Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

The current trend in next-generation exascale systems goes towards integrating a wide range of specialized (co-)processors into traditional supercomputers. However, the integration of different specialized devices increases the degree of heterogeneity and the complexity in programming such type of systems. Due to the efficiency of heterogeneous systems in terms of Watt and FLOPS per surface unit, opening the access of heterogeneous platforms to a wider range of users is an important problem to be tackled. In order to bridge the gap between heterogeneous systems and programmers, in this paper we propose a machine learning-based approach to learn heuristics for defining transformation strategies of a program transformation system. Our approach proposes a novel combination of reinforcement learning and classification methods to efficiently tackle the problems inherent to this type of systems. Preliminary results demonstrate the suitability of the approach for easing the programmability of heterogeneous systems.Comment: Part of the Program Transformation for Programmability in Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March 2016, 9 pages, LaTe

An Extensible Open-Source Compiler Infrastructure for Testing

Testing forms a critical part of the development process for large-scale software, and there is growing need for automated tools that can read, represent, analyze, and transform the application's source code to help carry out testing tasks. However, the support required to compile applications written in common general purpose languages is generally inaccessible to the testing research community. In this paper, we report on an extensible, open-source compiler infrastructure called ROSE, which is currently in development at Lawrence Livermore National Laboratory. ROSE specifically targets developers who wish to build source-based tools that implement customized analyses and optimizations for large-scale C, C++, and Fortran90 scientific computing applications (on the order of a million lines of code or more). However, much of this infrastructure can also be used to address problems in testing, and ROSE is by design broadly accessible to those without a formal compiler background. This paper details the interactions between testing of applications and the ways in which compiler technology can aid in the understanding of those applications. We emphasize the particular aspects of ROSE, such as support for the general analysis of whole programs, that are particularly well-suited to the testing research community and the scale of the problems that community solves

Design patterns for library optimizations

Abstract. We apply the notion of design patterns to optimizations performed by designers of software libraries, focusing especially on object-oriented numerical libraries. We formalize three design patterns that we have abstracted from many existing libraries and discuss the role of these formalizations as a tool for guiding compiler optimizers. These optimizers operate at a very high level that would otherwise be left unoptimized by traditional optimizers. Finally, we discuss the implementation of a design pattern-based compiler optimizer for C++ abstract data types

A Language for Specifying Compiler Optimizations for Generic Software

Compiler optimization is important to software performance, and modern processor architectures make optimization even more critical. However, many modern software applications use libraries providing high levels of abstraction. Such libraries often hinder effective optimization—the libraries are difficult to analyze using current compiler technology. For example, high-level libraries often use dynamic memory allocation and indirectly expressed control structures, such as iterator-based loops. Programs using these libraries often cannot achieve an optimal level of performance. On the other hand, software libraries have also been recognized as potentially aiding in program optimization. One proposed implementation of library-based optimization is to allow the library author, or a library user, to define custom analyses and optimizations. Only limited systems have been created to take advantage of this potential, however. One problem in creating a framework for defining new optimizations and analyses is how users are to specify them: implementing them by hand inside a compiler is difficult and prone to errors. Thus, a domain-specific language for library-based compiler optimizations would be beneficial. Many optimization specification languages have appeared in the literature, but they tend to be either limited in power or unnecessarily difficult to use. Therefore, I have designed, implemented, and evaluated the Pavilion language for specifying program analyses and optimizations, designed for library authors and users. These analyses and optimizations can be based on the implementation of a particular library, its use in a specific program, or on the properties of a broad range of types, expressed through concepts. The new system is intended to provide a high level of expressiveness, even though the intended users are unlikely to be compiler experts

Semantic and behavioral library transformations

While software methodology encourages the use of libraries and advocates architectures of layered libraries, in practice the composition of libraries is not always seamless and the combination of two well-designed libraries not necessarily well designed, since it could result in suboptimal call sequences, lost functionality, or avoidable overhead. In this paper we introduce Simplicissimus, a framework for rewrite-based source code transformations that allows for code replacement in a systematic and safe manner. We discuss the design and implementation of the framework and illustrate its functionality with applications in several areas.