Academic Journal

Autotuning and specialization: Speeding up matrix multiply for small matrices with compiler technology

التفاصيل البيبلوغرافية
العنوان: Autotuning and specialization: Speeding up matrix multiply for small matrices with compiler technology
المؤلفون: Jaewook Shin, Mary W. Hall, Jacqueline Chame, Chun Chen, Paul D. Hovland
المساهمون: The Pennsylvania State University CiteSeerX Archives
المصدر: http://www-unix.mcs.anl.gov/~jaewook/papers/iwapt09.pdf.
سنة النشر: 2009
المجموعة: CiteSeerX
الوصف: Autotuning technology has emerged recently as a systematic process for evaluating alternative implementations of a computation to select the best.performing solution for a particular architecture. Specialization optimizes code customized to a particular class of input data. This paper presents a compiler optimization approach that combines novel autotuning compiler technology with specialization for expected data set sizes of key computations, focused on matrix multiplication of small matrices. We describe compiler techniques developed for this approach, including the interface to a polyhedral transformation system for generating specialized code and the heuristics used to prune the enormous search space of alternative implementations. We demonstrate significantly better performance than directly using libraries such as GOTO, ATLAS and ACML BLAS that are not specifically optimized for the problem sizes on hand. In a case study of nek5000, a spectral element based code that extensively uses the specialized matrix multiply, we demonstrate a performance improvement for the full application of 36%.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.155.3869; http://www-unix.mcs.anl.gov/~jaewook/papers/iwapt09.pdf
الاتاحة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.155.3869
http://www-unix.mcs.anl.gov/~jaewook/papers/iwapt09.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
رقم الانضمام: edsbas.523BB718
قاعدة البيانات: BASE