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Colloquium - Strout

Introducing the Sparse Polyhedral Framework
Colorado State University

Loops often dominate the execution time of applications. Various transformation frameworks have been developed to enable the automatic compile-time transformation of loops. Many of the existing models fit within the polyhedral framework and although they are quite powerful, they are restricted to compile-time transformations and loop bounds and memory accesses that are affine or can be approximated as affine.

In this talk, I will present the Sparse Polyhedral Framework (SPF). The SPF builds on the polyhedral programming model, but is also capable of expressing and supporting the code generation for run-time reordering transformations implemented with inspector/executor strategies. I will then discuss the idea of abstractions for exposing transformation frameworks in performance programmer models.

Michelle Mills Strout is an assistant professor of computer science at Colorado State University. She obtained her PhD in Computer Science from the University of California, San Diego in June 2003. In 2008, Michelle received a CAREER Award from the National Science Foundation for her research in parallelization techniques for irregular applications, such as molecular dynamics simulations. Her main research area is high performance computing and her research interests include compilers and run-time systems, scientific computing, and software engineering.

Hosted by Amer Diwan.

Department of Computer Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
May 5, 2012 (14:13)