PetaFLOPS Computing.

The article discusses the use of PetaFLOPS computers in understanding the functions of biological molecules. PetaFLOPS computers are capable of performing a thousand trillion mathematical operations per second and are 25 times faster than the largest supercomputers. The effort to create PetaFLOPS co...

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Publicado en:Communications of the ACM Vol. 47; no. 11; pp. 42 - 46
Autores principales: Ebisuzaki, Toshikazu, Germain, Robert, Taiji, Makoto
Formato: Artículo
Publicado: Association for Computing Machinery Nov2004
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: PetaFLOPS Computing.
      aug:
        au:
          Ebisuzaki, Toshikazu
          Germain, Robert
          Taiji, Makoto
        affil:
          Chief Scientist, Institute of Physical and Chemical Research, Wako, Japan.
          Project Director, MD-GRAPE, Peta Computing Institute, Ltd., Wako, Japan.
          Manager, Biomolecular Dynamics and Scalable Modeling, IBM Thomas J. Watson Research Center; Yorktown Heights, NY.
          Team Leader, High Performance Biocomputing Research, Institute of Physical and Chemical Research in Wako, Japan.
      su:
        Petaflops computers
        Biomolecules
        International Business Machines Corp.
        Microprocessors
        Parallel programming
        Supercomputers
      sug:
        subj:
          Petaflops computers
          Biomolecules
          International Business Machines Corp.
          Microprocessors
          Parallel programming
          Supercomputers
      ab: The article discusses the use of PetaFLOPS computers in understanding the functions of biological molecules. PetaFLOPS computers are capable of performing a thousand trillion mathematical operations per second and are 25 times faster than the largest supercomputers. The effort to create PetaFLOPS computing systems to study complex biological phenomena faces three critical challenges: money; the physical aspects of providing electricity and cooling for very large systems; and the algorithms needed to create programs that will run effectively on a PetaFLOPS scale computer. Due to the challenges of developing applications that will scale to run on a PetaFLOPS computer, and due to the practical problems of managing power and cooling, current efforts to build PetaFLOPS computing systems take different strategies from those employed in the design of most large supercomputers. The IBM Corp.'s Blue Gene Project is leveraging low-power chip technologies developed for embedded microprocessors to achieve extremely high ratios of performance to power dissipated while combining these CPUs with a highly specialized interconnect that greatly facilitates large-scale parallel programming.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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