Superblock scheduling using genetic programming for embedded systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Mahajan:2008:ieeeICCI,
  author =       "Anjali Mahajan and M S Ali",
  title =        "Superblock scheduling using genetic programming for
                 embedded systems",
  booktitle =    "7th IEEE International Conference on Cognitive
                 Informatics, ICCI 2008",
  year =         "2008",
  month =        aug,
  pages =        "261--266",
  keywords =     "genetic algorithms, genetic programming, NP-complete
                 problem, embedded system, instruction scheduling,
                 optimally scheduling instruction, optimized compiler,
                 processor architecture, superblock scheduling, embedded
                 systems, optimising compilers, scheduling",
  DOI =          "doi:10.1109/COGINF.2008.4639177",
  size =         "6 pages",
  abstract =     "Instruction scheduling is an important issue in the
                 compiler optimization for embedded systems. The
                 instruction scheduling problem is mainly solved
                 heuristically since finding an optimal solution
                 requires significant computational resources and, in
                 general, the problem of optimally scheduling
                 instructions is known to be NP-Complete. The
                 development of processors with pipelines and multiple
                 functional units has increased the demands on compiler
                 writers to write complex instruction scheduling
                 algorithms. These algorithms are required to ensure
                 that the most efficient use of resources, i.e. the
                 functional units and pipelines of the processor, is
                 made due to the increased complexity of processor
                 architectures. In this paper, the specific problem of
                 automatically creating instruction scheduling
                 heuristics is addressed.",
  notes =        "http://www.eecs.harvard.edu/hube/research/machsuif.html
                 broken Sep 2014.

                 Also known as \cite{4639177}",
}

Genetic Programming entries for Anjali Mahajan M S Ali

Citations