- 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, genetic improvement, 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}",
