Provided by: Association for Computing Machinery
Date Added: Jan 2013
Most scientific computations serve to apply mathematical operations to a set of preconceived data structures, e.g., matrices, vectors, and grids. In this paper, the authors use a number of widely used matrix computations from the LINPACK library to demonstrate that complex internal organizations of data structures can severely degrade the effectiveness of compiler optimizations. They then present a data-layout-oblivious optimization methodology, where by isolating an abstract representation of the computations from complex implementation details of their data, they enable these computations to be much more accurately analyzed and optimized through varying state-of-the-art compiler technologies.