Extendable pattern-oriented optimization directives

Author:

Cui Huimin1,Xue Jingling2,Wang Lei1,Yang Yang1,Feng Xiaobing1,Fan Dongrui1

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

2. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia

Abstract

Algorithm-specific, that is, semantic-specific optimizations have been observed to bring significant performance gains, especially for a diverse set of multi/many-core architectures. However, current programming models and compiler technologies for the state-of-the-art architectures do not exploit well these performance opportunities. In this article, we propose a pattern-making methodology that enables algorithm-specific optimizations to be encapsulated into “optimization patterns”. Such optimization patterns are expressed in terms of preprocessor directives so that simple annotations can result in significant performance improvements. To validate this new methodology, a framework, named EPOD, is developed to map these directives into the underlying optimization schemes for a particular architecture. It is difficult to create an exact performance model to determine an optimal or near-optimal optimization scheme (including which optimizations to apply and in which order) for a specific application, due to the complexity of applications and architectures. However, it is trackable to build individual optimization components and let compiler developers synthesize an optimization scheme from these components. Therefore, our EPOD framework provides an Optimization Programming Interface (OPI) for compiler developers to define new optimization schemes. Thus, new patterns can be integrated into EPOD in a flexible manner. We have identified and implemented a number of optimization patterns for three representative computer platforms. Our experimental results show that a pattern-guided compiler can outperform the state-of-the-art compilers and even achieve performance as competitive as hand-tuned code. Therefore, such a pattern-making methodology represents an encouraging direction for domain experts' experience and knowledge to be integrated into general-purpose compilers.

Funder

Australian Research Council

National Natural Science Foundation of China

National Science and Technology Major Projects

Ministry of Science and Technology of the People's Republic of China

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

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