Temporal Locality Optimizations for Parallel Object-oriented Scientific Frameworks

نویسندگان

  • Federico Bassetti
  • Kei Davis
  • Dan Quinlan
چکیده

High-performance scientiic computing relies increasingly on high-level large-scale object-oriented software frameworks to manage both algorithmic complexity and the complexities of parallelism: distributed data management, process management, inter-process communication, and load balancing. This encapsu-lation of data management, together with the prescribed semantics of a typical fundamental component of such object-oriented frameworks|a parallel or serial array-class library|provides an opportunity for increasingly sophisticated compile-time optimization techniques. This paper describes a technique for introducing cache blocking suitable for certain classes of numerical algorithms, demonstrates and analyzes the resulting performance gains, and indicates how this optimizing transformation is being automated.

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تاریخ انتشار 2007