SC13 Home > SC13 Schedule > SC13 Presentation - Empirical Search to Optimize Matrix Computation

SCHEDULE: NOV 16-22, 2013

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Empirical Search to Optimize Matrix Computation

SESSION: Doctoral Showcase - Dissertation Research

EVENT TYPE: Doctoral Showcase - Dissertation Research Showcase

TIME: 11:45AM - 12:00PM

SESSION CHAIR: Alistair Rendell

Presenter(s):Thomas Nelson


High performance linear algebra is an important component to many numerical applications. Efficient matrix computation requires careful optimization based on application and hardware, typically a time consuming process. Today most scientific applications use BLAS (Basic Linear Algebra Subprograms) to provide high-performance linear algebra computation. This research presents an alternative approach, based on an empirical search strategy for linear algebra optimization. It uses Build-to-Order BLAS, a domain-specific language for linear algebra that produces highly-optimized multicore C code as output. This approach maintains a high-level understanding of the operations, which allows more aggressive code transformation. The search is based on a highly-tuned genetic algorithm, which performs global search over a transformation space while maintaining correctness and using application-specific heuristics. Our results show significant speedups compared to traditional library-based approaches for many matrix kernels.

Chair/Presenter Details:

Alistair Rendell (Chair) - Australian National University

Thomas Nelson - University of Colorado Boulder

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