An Approach Based on a DSL plus API for Programming Runtime Adaptivity and Autotuning Concerns

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Carvalho, T (Author) Other; João M. P. Cardoso (Author) FEUP

Conference proceedings International

Title: Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018, Pau, France, April 09-13, 2018

Pages: 1211-1220

33rd Annual ACM Symposium on Applied Computing, SAC 2018

9 April 2018 through 13 April 2018

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00N-ZR5

DOI: 10.1145/3167132.3167263

Abstract (EN): In the context of compiler optimizations, tuning of parameters and selection of algorithms, runtime adaptivity and autotuning are becoming increasingly important, especially due to the complexity of applications, workloads, computing devices and execution environments. For identifying and specifying adaptivity, different phases are required: analysis of program hotspots and adaptivity opportunities, code restructuring, and programming of adaptivity strategies. These phases usually require different tools and modications to the source code that may result in difficult to maintain and error prone code. This paper presents a flexible approach to support the different phases when developing adaptive applications. The approach is based on a single domain-specific language (DSL), able to specify and evaluate multiple strategies and to maintain a separation of concerns. We describe the requirements and the design of the DSL, an accompanying API, and of a Java-to-Java compiler that implements the approach. In addition, we present and evaluate the use of the approach to specify runtime adaptivity strategies in the context of Java programs, especially when considering runtime autotuning of optimization parameters and runtime selection of algorithms. Although simple, the case studies shown truly demonstrate the main advantages of the approach in terms of the programming model and of the performance impact.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10