Programming Distributed Memory Computers with Sequential Programming Abstractions: High Level Optimizing Compilers
January 14, 2009
New representations of linear algebra kernels in a high level optimizer expand the scope of programs that can be optimized and the range of hardware targets for such optimizations. Programs that conform to an extended static control form are expressed to the compiler in sequential C. A polyhedral abstraction exposes parallelism to a greater degree than available using previous high-level compiler abstractions, and allows ILP formulations of optimizations that balance parallelism with locality of reference. The resulting form can be rendered to emerging architectures with accelerators, explicitly managed communication and local memories, as well as to classic SMP abstractions/OpenMP. The R-Stream compiler provides an implementation of these optimizations linked to a powerful C-language infrastructure to allow using this tool with a conventional programming language without special extensions. This seminar will discuss the polyhedral abstractions, the implementation, current results, challenges, limitations and opportunities enabled by this new compiler technology.
About NERSC and Berkeley Lab
The National Energy Research Scientific Computing Center (NERSC) is the primary high-performance computing facility for scientific research sponsored by the U.S. Department of Energy's Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves more than 4,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. DOE Office of Science. For more information about computing sciences at Berkeley Lab, please visit www.lbl.gov/cs.
