2012 21st International Conference on Parallel Architectures and Compilation Techniques (PACT) (2012)
Minneapolis, MN, USA
Sept. 19, 2012 to Sept. 23, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/
Huimin Cui , SKL Computer Architecture, Institute of Computing Technology, CAS, Beijing, China
Qing Yi , Depart. of Computer Science, University of Texas at San Antonio, USA
Jingling Xue , School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
Xiaobing Feng , SKL Computer Architecture, Institute of Computing Technology, CAS, Beijing, China
Most scientific computations serve to apply mathematical operations to a set of preconceived data structures, e.g., matrices, vectors, and grids. In this paper, we 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 compilers optimizations. We then present a data layout oblivious optimization methodology, where by isolating an abstract representation of computations from complex implementation details of their data, we enable these computations to be much more accurately analyzed and optimized through varying state-of-the-art compiler technologies.
Optimization, Matrix converters, Data structures, Layout, Kernel, Pluto, Organizations
H. Cui, Q. Yi, J. Xue and X. Feng, "Layout-oblivious optimization for matrix computations," 2012 21st International Conference on Parallel Architectures and Compilation Techniques (PACT), Minneapolis, MN, USA, 2012, pp. 429-430.